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1401.3274
Deepjyoti Deka
Deepjyoti Deka, Ross Baldick, and Sriram Vishwanath
Hidden Attacks on Power Grid: Optimal Attack Strategies and Mitigation
null
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Real time operation of the power grid and synchronism of its different elements require accurate estimation of its state variables. Errors in state estimation will lead to sub-optimal Optimal Power Flow (OPF) solutions and subsequent increase in the price of electricity in the market or, potentially overload and create line outages. This paper studies hidden data attacks on power systems by an adversary trying to manipulate state estimators. The adversary gains control of a few meters, and is able to introduce spurious measurements in them. The paper presents a polynomial time algorithm using min-cut calculations to determine the minimum number of measurements an adversary needs to manipulate in order to perform a hidden attack. Greedy techniques are presented to aid the system operator in identifying critical measurements for protection to prevent such hidden data attacks. Secure PMU placement against data attacks is also discussed and an algorithm for placing PMUs for this purpose is developed. The performances of the proposed algorithms are shown through simulations on IEEE test cases.
[ { "created": "Tue, 14 Jan 2014 18:26:36 GMT", "version": "v1" } ]
2014-01-15
[ [ "Deka", "Deepjyoti", "" ], [ "Baldick", "Ross", "" ], [ "Vishwanath", "Sriram", "" ] ]
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1401.3276
Juan Betancort-Rijo
Juan Betancort-Rijo (1,2) and Felipe Jimenez Ibarra (2) ((1) Instituto de Astrofisica de Canarias, La Laguna, Tenerife, Spain (2) Departamento de Astrofisica, Universidad de La Laguna, Tenerife, Spain)
Einstein's first gravitational field equation 101 years latter
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null
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gr-qc physics.hist-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We review and strengthen the arguments given by Einstein to derive his first gravitational field equation for static fields and show that, although it was ultimately rejected, it follows from General Relativity (GR) for negligible pressure. Using this equation and considerations folowing directly from the equivalence principle (EP), we show how Schwarzschild metric and other vacum metrics can be obtained immediately. With this results and some basic principles, we obtain the metric in the general spherically symmetric case and the corresponding hydrostatic equilibrium equation. For this metrics we obtain the motion equations in a simple and exact manner that clearly shows the three sources of difference (implied by various aspects of the EP) with respect to the Newtonian case and use them to study the classical tests of GR. We comment on the origin of the problems of Einstein first theory of gravity and discuss how, by removing it the theory could be made consistent and extended to include rotations, we also comments on various conceptual issues of GR as the origin of the gravitational effect of pressure.
[ { "created": "Fri, 10 Jan 2014 18:58:12 GMT", "version": "v1" } ]
2014-01-15
[ [ "Betancort-Rijo", "Juan", "" ], [ "Ibarra", "Felipe Jimenez", "" ] ]
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1401.3277
Diego Valsesia
Diego Valsesia, Enrico Magli
A Novel Rate Control Algorithm for Onboard Predictive Coding of Multispectral and Hyperspectral Images
null
null
10.1109/TGRS.2013.2296329
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Predictive coding is attractive for compression onboard of spacecrafts thanks to its low computational complexity, modest memory requirements and the ability to accurately control quality on a pixel-by-pixel basis. Traditionally, predictive compression focused on the lossless and near-lossless modes of operation where the maximum error can be bounded but the rate of the compressed image is variable. Rate control is considered a challenging problem for predictive encoders due to the dependencies between quantization and prediction in the feedback loop, and the lack of a signal representation that packs the signal's energy into few coefficients. In this paper, we show that it is possible to design a rate control scheme intended for onboard implementation. In particular, we propose a general framework to select quantizers in each spatial and spectral region of an image so as to achieve the desired target rate while minimizing distortion. The rate control algorithm allows to achieve lossy, near-lossless compression, and any in-between type of compression, e.g., lossy compression with a near-lossless constraint. While this framework is independent of the specific predictor used, in order to show its performance, in this paper we tailor it to the predictor adopted by the CCSDS-123 lossless compression standard, obtaining an extension that allows to perform lossless, near-lossless and lossy compression in a single package. We show that the rate controller has excellent performance in terms of accuracy in the output rate, rate-distortion characteristics and is extremely competitive with respect to state-of-the-art transform coding.
[ { "created": "Tue, 14 Jan 2014 18:45:29 GMT", "version": "v1" } ]
2014-01-15
[ [ "Valsesia", "Diego", "" ], [ "Magli", "Enrico", "" ] ]
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1401.3280
Krzysztof Bar
Krzysztof Bar and Jamie Vicary
Groupoid Semantics for Thermal Computing
We describe a groupoid model for thermodynamic computation, and a quantization procedure that turns encrypted communication into quantum teleportation. Everything is done using higher category theory
null
null
null
cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A groupoid semantics is presented for systems with both logical and thermal degrees of freedom. We apply this to a syntactic model for encryption, and obtain an algebraic characterization of the heat produced by the encryption function, as predicted by Landauer's principle. Our model has a linear representation theory that reveals an underlying quantum semantics, giving for the first time a functorial classical model for quantum teleportation and other quantum phenomena.
[ { "created": "Tue, 14 Jan 2014 18:48:25 GMT", "version": "v1" }, { "created": "Thu, 16 Jan 2014 11:55:56 GMT", "version": "v2" } ]
2014-01-17
[ [ "Bar", "Krzysztof", "" ], [ "Vicary", "Jamie", "" ] ]
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1401.3281
Didier Sornette
Didier Sornette and Peter Cauwels
A Creepy World
16 pages with 5 figures. Notenstein White Paper Series, November 2013
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physics.soc-ph q-fin.GN
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Using the mechanics of creep in material sciences as a metaphor, we present a general framework to understand the evolution of financial, economic and social systems and to construct scenarios for the future. In a nutshell, highly non-linear out-of-equilibrium systems subjected to exogenous perturbations tend to exhibit a long phase of slow apparent stable evolution, which are nothing but slow maturations towards instabilities, failures and changes of regimes. With examples from history where a small event had a cataclysmic consequence, we propose a novel view of the current state of the world via the logical scenarios that derive, avoiding the traps of an illusionary stability and simple linear extrapolation. The endogenous scenarios are "muddling along", "managing through" and "blood red abyss". The exogenous scenarios are "painful adjustment" and "golden east".
[ { "created": "Tue, 14 Jan 2014 18:48:36 GMT", "version": "v1" } ]
2014-01-15
[ [ "Sornette", "Didier", "" ], [ "Cauwels", "Peter", "" ] ]
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1401.3289
Krishnendu Chatterjee
Krishnendu Chatterjee and Laurent Doyen and Sumit Nain and Moshe Y. Vardi
The Complexity of Partial-observation Stochastic Parity Games With Finite-memory Strategies
null
null
null
null
cs.LO cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider two-player partial-observation stochastic games on finite-state graphs where player 1 has partial observation and player 2 has perfect observation. The winning condition we study are \omega-regular conditions specified as parity objectives. The qualitative-analysis problem given a partial-observation stochastic game and a parity objective asks whether there is a strategy to ensure that the objective is satisfied with probability~1 (resp. positive probability). These qualtitative-analysis problems are known to be undecidable. However in many applications the relevant question is the existence of finite-memory strategies, and the qualitative-analysis problems under finite-memory strategies was recently shown to be decidable in 2EXPTIME. We improve the complexity and show that the qualitative-analysis problems for partial-observation stochastic parity games under finite-memory strategies are EXPTIME-complete; and also establish optimal (exponential) memory bounds for finite-memory strategies required for qualitative analysis.
[ { "created": "Tue, 14 Jan 2014 19:14:27 GMT", "version": "v1" } ]
2014-01-15
[ [ "Chatterjee", "Krishnendu", "" ], [ "Doyen", "Laurent", "" ], [ "Nain", "Sumit", "" ], [ "Vardi", "Moshe Y.", "" ] ]
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1401.3292
Luo Yongming
Y. M. Luo, C. Zhou, C. Won and Y. Z. Wu
Effect of Dzyaloshinskii Moriya interaction on magnetic vortex
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cond-mat.mes-hall physics.comp-ph
http://creativecommons.org/licenses/by/3.0/
The effect of the Dzyaloshinskii Moriya interaction on the vortex in magnetic microdisk was investigated by micro magnetic simulation based on the Landau Lifshitz Gilbert equation. Our results show that the DM interaction modifies the size of the vortex core, and also induces an out of plane magnetization component at the edge and inside the disk. The DM interaction can destabilizes one vortex handedness, generate a bias field to the vortex core and couple the vortex polarity and chirality. This DM-interaction-induced coupling can therefore provide a new way to control vortex polarity and chirality.
[ { "created": "Mon, 13 Jan 2014 15:08:23 GMT", "version": "v1" } ]
2014-01-15
[ [ "Luo", "Y. M.", "" ], [ "Zhou", "C.", "" ], [ "Won", "C.", "" ], [ "Wu", "Y. Z.", "" ] ]
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1401.3301
Caroline Japhet
Fran\c{c}ois Cuvelier, Caroline Japhet, Gilles Scarella
An efficient way to assemble finite element matrices in vector languages
null
null
null
null
cs.MS cs.NA math.NA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Efficient Matlab codes in 2D and 3D have been proposed recently to assemble finite element matrices. In this paper we present simple, compact and efficient vectorized algorithms, which are variants of these codes, in arbitrary dimension, without the use of any lower level language. They can be easily implemented in many vector languages (e.g. Matlab, Octave, Python, Scilab, R, Julia, C++ with STL,...). The principle of these techniques is general, we present it for the assembly of several finite element matrices in arbitrary dimension, in the P1 finite element case. We also provide an extension of the algorithms to the case of a system of PDE's. Then we give an extension to piecewise polynomials of higher order. We compare numerically the performance of these algorithms in Matlab, Octave and Python, with that in FreeFEM++ and in a compiled language such as C. Examples show that, unlike what is commonly believed, the performance is not radically worse than that of C : in the best/worst cases, selected vector languages are respectively 2.3/3.5 and 2.9/4.1 times slower than C in the scalar and vector cases. We also present numerical results which illustrate the computational costs of these algorithms compared to standard algorithms and to other recent ones.
[ { "created": "Tue, 14 Jan 2014 19:36:39 GMT", "version": "v1" }, { "created": "Fri, 19 Jun 2015 09:17:43 GMT", "version": "v2" } ]
2015-06-22
[ [ "Cuvelier", "François", "" ], [ "Japhet", "Caroline", "" ], [ "Scarella", "Gilles", "" ] ]
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1401.3303
Francesco Terranova
F. Terranova
Particle acceleration in sub-cycle optical cells
13 pages, 7 figures. Version to appear in PRSTAB
Phys. Rev. ST Accel. Beams 17, 071301 (2014)
10.1103/PhysRevSTAB.17.071301
null
physics.optics hep-ex physics.acc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A single laser pulse with spot size smaller than half its wavelength ($w_0 < \lambda/2$) can provide a net energy gain to ultra-relativistic particles. In this paper, we discuss the properties of an optical cell consisting of $N$ sub-cycle pulses that propagate in the direction perpendicular to the electron motion. We show that the energy gain produced by the cell is proportional to $N$ and it is sizable even for $\mathcal{O}(1\mathrm{~TW})$ pulses.
[ { "created": "Tue, 14 Jan 2014 19:43:16 GMT", "version": "v1" }, { "created": "Mon, 7 Jul 2014 17:49:01 GMT", "version": "v2" } ]
2014-07-23
[ [ "Terranova", "F.", "" ] ]
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1401.3307
Yongge Wang
Yongge Wang
On the Design of LIL Tests for (Pseudo) Random Generators and Some Experimental Results
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null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
NIST SP800-22 (2010) proposes the state of art testing suite for (pseudo) random generators to detect deviations of a binary sequence from randomness. On the one hand, as a counter example to NIST SP800-22 test suite, it is easy to construct functions that are considered as GOOD pseudorandom generators by NIST SP800-22 test suite though the output of these functions are easily distinguishable from the uniform distribution. Thus these functions are not pseudorandom generators by definition. On the other hand, NIST SP800-22 does not cover some of the important laws for randomness. Two fundamental limit theorems about random binary strings are the central limit theorem and the law of the iterated logarithm (LIL). Several frequency related tests in NIST SP800-22 cover the central limit theorem while no NIST SP800-22 test covers LIL. This paper proposes techniques to address the above challenges that NIST SP800-22 testing suite faces. Firstly, we propose statistical distance based testing techniques for (pseudo) random generators to reduce the above mentioned Type II errors in NIST SP800-22 test suite. Secondly, we propose LIL based statistical testing techniques, calculate the probabilities, and carry out experimental tests on widely used pseudorandom generators by generating around 30TB of pseudorandom sequences. The experimental results show that for a sample size of 1000 sequences (2TB), the statistical distance between the generated sequences and the uniform distribution is around 0.07 (with $0$ for statistically indistinguishable and $1$ for completely distinguishable) and the root-mean-square deviation is around 0.005.
[ { "created": "Tue, 14 Jan 2014 19:46:30 GMT", "version": "v1" } ]
2014-01-15
[ [ "Wang", "Yongge", "" ] ]
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1401.3308
Alexandre Pinlou
Pascal Ochem, Alexandre Pinlou, Sagnik Sen
Homomorphisms of signed planar graphs
null
null
null
null
cs.DM math.CO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Signed graphs are studied since the middle of the last century. Recently, the notion of homomorphism of signed graphs has been introduced since this notion captures a number of well known conjectures which can be reformulated using the definitions of signed homomorphism. In this paper, we introduce and study the properties of some target graphs for signed homomorphism. Using these properties, we obtain upper bounds on the signed chromatic numbers of graphs with bounded acyclic chromatic number and of signed planar graphs with given girth.
[ { "created": "Tue, 14 Jan 2014 19:53:26 GMT", "version": "v1" } ]
2014-01-15
[ [ "Ochem", "Pascal", "" ], [ "Pinlou", "Alexandre", "" ], [ "Sen", "Sagnik", "" ] ]
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1401.3309
Spencer Backman
Spencer Backman
Riemann-Roch Theory for Graph Orientations
35 pages, 8 figures, further revisions and updated references
null
null
null
math.CO cs.DM math.AG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We develop a new framework for investigating linear equivalence of divisors on graphs using a generalization of Gioan's cycle--cocycle reversal system for partial orientations. An oriented version of Dhar's burning algorithm is introduced and employed in the study of acyclicity for partial orientations. We then show that the Baker--Norine rank of a partially orientable divisor is one less than the minimum number of directed paths which need to be reversed in the generalized cycle--cocycle reversal system to produce an acyclic partial orientation. These results are applied in providing new proofs of the Riemann--Roch theorem for graphs as well as Luo's topological characterization of rank-determining sets. We prove that the max-flow min-cut theorem is equivalent to the Euler characteristic description of orientable divisors and extend this characterization to the setting of partial orientations. Furthermore, we demonstrate that $Pic^{g-1}(G)$ is canonically isomorphic as a $Pic^{0}(G)$-torsor to the equivalence classes of full orientations in the cycle--cocycle reversal system acted on by directed path reversals. Efficient algorithms for computing break divisors and constructing partial orientations are presented.
[ { "created": "Tue, 14 Jan 2014 19:55:32 GMT", "version": "v1" }, { "created": "Mon, 7 Jul 2014 00:48:46 GMT", "version": "v2" }, { "created": "Wed, 7 Oct 2015 08:37:20 GMT", "version": "v3" }, { "created": "Fri, 14 Apr 2017 15:50:44 GMT", "version": "v4" } ]
2017-04-17
[ [ "Backman", "Spencer", "" ] ]
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1401.3316
Petr Jizba
Petr Jizba and Jan Korbel
Multifractal Diffusion Entropy Analysis: Optimal Bin Width of Probability Histograms
25 pages, 7 figures, LaTeX with the Elsevier article class, substantially revised version
Physica A 413 (2014) 438-458
10.1016/j.physa.2014.07.008
null
q-fin.ST math-ph math.MP physics.data-an
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In the framework of Multifractal Diffusion Entropy Analysis we propose a method for choosing an optimal bin-width in histograms generated from underlying probability distributions of interest. The method presented uses techniques of R\'{e}nyi's entropy and the mean squared error analysis to discuss the conditions under which the error in the multifractal spectrum estimation is minimal. We illustrate the utility of our approach by focusing on a scaling behavior of financial time series. In particular, we analyze the S&P500 stock index as sampled at a daily rate in the time period 1950-2013. In order to demonstrate a strength of the method proposed we compare the multifractal $\delta$-spectrum for various bin-widths and show the robustness of the method, especially for large values of $q$. For such values, other methods in use, e.g., those based on moment estimation, tend to fail for heavy-tailed data or data with long correlations. Connection between the $\delta$-spectrum and R\'{e}nyi's $q$ parameter is also discussed and elucidated on a simple example of multiscale time series.
[ { "created": "Tue, 14 Jan 2014 20:18:27 GMT", "version": "v1" }, { "created": "Wed, 12 Mar 2014 21:06:35 GMT", "version": "v2" } ]
2014-07-25
[ [ "Jizba", "Petr", "" ], [ "Korbel", "Jan", "" ] ]
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1401.3319
Vadim Markel
Howard W. Levinson and Vadim A. Markel
Nonlinear inverse problem by T-matrix completion. I. Theory
This is Part I of a paper series containing theory only. Part II contains simulations and is available as arXiv:1505.06777 [math-ph]. Accepted in this form to Phys. Rev. E
Phys. Rev. E 94, 043317 (2016)
10.1103/PhysRevE.94.043317
null
math-ph math.MP physics.med-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose a conceptually new method for solving nonlinear inverse scattering problems (ISPs) such as are commonly encountered in tomographic ultrasound imaging, seismology and other applications. The method is inspired by the theory of nonlocality of physical interactions and utilizes the relevant formalism. We formulate the ISP as a problem whose goal is to determine an unknown interaction potential $V$ from external scattering data. Although we seek a local (diagonally-dominated) $V$ as the solution to the posed problem, we allow $V$ to be nonlocal at the intermediate stages of iterations. This allows us to utilize the one-to-one correspondence between $V$ and the T-matrix of the problem, $T$. Here it is important to realize that not every $T$ corresponds to a diagonal $V$ and we, therefore, relax the usual condition of strict diagonality (locality) of $V$. An iterative algorithm is proposed in which we seek $T$ that is (i) compatible with the measured scattering data and (ii) corresponds to an interaction potential $V$ that is as diagonally-dominated as possible. We refer to this algorithm as to the data-compatible T-matrix completion (DCTMC). This paper is Part I in a two-part series and contains theory only. Numerical examples of image reconstruction in a strongly nonlinear regime are given in Part II. The method described in this paper is particularly well suited for very large data sets that become increasingly available with the use of modern measurement techniques and instrumentation.
[ { "created": "Tue, 14 Jan 2014 20:24:46 GMT", "version": "v1" }, { "created": "Wed, 27 May 2015 14:46:45 GMT", "version": "v2" }, { "created": "Tue, 27 Sep 2016 08:57:19 GMT", "version": "v3" } ]
2016-11-02
[ [ "Levinson", "Howard W.", "" ], [ "Markel", "Vadim A.", "" ] ]
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1401.3324
Jason Heebl
Jason D. Heebl, Erin M. Thomas, Robert P. Penno, Anthony Grbic
Comprehensive Analysis and Measurement of Frequency-Tuned and Impedance-Tuned Wireless Non-Radiative Power Transfer Systems
11 pages, 16 figures. This article has been accepted into IEEE Antennas and Propagation Magazine
null
10.1109/MAP.2014.6971924
null
cs.OH
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper theoretically and experimentally investigates frequency-tuned and impedance-tuned wireless non-radiative power transfer (WNPT) systems. Closed-form expressions for the efficiencies of both systems, as a function of frequency and system (circuit) parameters, are presented. In the frequency-tuned system, the operating frequency is adjusted to compensate for changes in mutual inductance that occur for variations of transmitter and receiver loop positions. Frequency-tuning is employed for a range of distances over which the loops are strongly coupled. In contrast, the impedance-tuned system employs varactor-based matching networks to compensate for changes in mutual inductance and achieve a simultaneous conjugate impedance match over a range of distances. The frequency-tuned system is simpler to implement, while the impedance-tuned system is more complex but can achieve higher efficiencies. Both of the experimental WNPT systems studied employ resonant shielded loops as transmitting and receiving devices.
[ { "created": "Tue, 14 Jan 2014 20:37:27 GMT", "version": "v1" } ]
2015-01-23
[ [ "Heebl", "Jason D.", "" ], [ "Thomas", "Erin M.", "" ], [ "Penno", "Robert P.", "" ], [ "Grbic", "Anthony", "" ] ]
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1401.3325
Arno Pauly
St\'ephane Le Roux and Arno Pauly
Equilibria in multi-player multi-outcome infinite sequential games
Section 8 of Version 1 is no longer part of the article, and will in time be made available elsewhere; Section 7 of Version 2 has been expanded into http://arxiv.org/abs/1602.08912
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null
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cs.LO cs.GT math.GN
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We investigate the existence of certain types of equilibria (Nash, $\varepsilon$-Nash, subgame perfect, $\varepsilon$-subgame perfect, Pareto-optimal) in multi-player multi-outcome infinite sequential games. We use two fundamental approaches: one requires strong topological restrictions on the games, but produces very strong existence results. The other merely requires some very basic determinacy properties to still obtain some existence results. Both results are transfer results: starting with the existence of some equilibria for a small class of games, they allow us to conclude the existence of some type of equilibria for a larger class. To make the abstract results more concrete, we investigate as a special case infinite sequential games with real-valued payoff functions. Depending on the class of payoff functions (continuous, upper semi-continuous, Borel) and whether the game is zero-sum, we obtain various existence results for equilibria. Our results hold for games with two or up to countably many players.
[ { "created": "Tue, 14 Jan 2014 20:37:39 GMT", "version": "v1" }, { "created": "Wed, 18 Nov 2015 18:22:03 GMT", "version": "v2" }, { "created": "Wed, 16 Mar 2016 21:14:09 GMT", "version": "v3" } ]
2016-03-18
[ [ "Roux", "Stéphane Le", "" ], [ "Pauly", "Arno", "" ] ]
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1401.3331
Dani Korpi
Dani Korpi, Sathya Venkatasubramanian, Taneli Riihonen, Lauri Anttila, Strasdosky Otewa, Clemens Icheln, Katsuyuki Haneda, Sergei Tretyakov, Mikko Valkama, Risto Wichman
Advanced Self-interference Cancellation and Multiantenna Techniques for Full-Duplex Radios
Presented in 47th Annual Asilomar Conference on Signals, Systems, and Computers, 2013
null
null
null
cs.OH
http://creativecommons.org/licenses/by/3.0/
In an in-band full-duplex system, radios transmit and receive simultaneously in the same frequency band at the same time, providing a radical improvement in spectral efficiency over a half-duplex system. However, in order to design such a system, it is necessary to mitigate the self-interference due to simultaneous transmission and reception, which seriously limits the maximum transmit power of the full-duplex device. Especially, large differences in power levels in the receiver front-end sets stringent requirements for the linearity of the transceiver electronics. We present an advanced architecture for a compact full-duplex multiantenna transceiver combining antenna design with analog and digital cancellation, including both linear and nonlinear signal processing.
[ { "created": "Tue, 14 Jan 2014 12:41:22 GMT", "version": "v1" } ]
2014-01-16
[ [ "Korpi", "Dani", "" ], [ "Venkatasubramanian", "Sathya", "" ], [ "Riihonen", "Taneli", "" ], [ "Anttila", "Lauri", "" ], [ "Otewa", "Strasdosky", "" ], [ "Icheln", "Clemens", "" ], [ "Haneda", "Katsuyuki", "" ], [ "Tretyakov", "Sergei", "" ], [ "Valkama", "Mikko", "" ], [ "Wichman", "Risto", "" ] ]
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1401.3332
Raimund Strauss
R. Strauss, G. Angloher, A. Bento, C. Bucci, L. Canonica, W. Carli, C. Ciemniak, A. Erb, F.v. Feilitzsch, P. Gorla, A. G\"utlein, H. Hagn, D. Hauff, D. Hellgartner, J. Jochum, H. Kraus, J.-C. Lanfranchi, J. Loebell, A. M\"unster, F. Petricca, W. Potzel, F. Pr\"obst, F. Reindl, S. Roth, K. Rottler, C. Sailer, K. Sch\"affner, J. Schieck, S. Scholl, S. Sch\"onert, W. Seidel, M.v. Sivers, L. Stodolsky, C. Strandhagen, A. Tanzke, M. Uffinger, A. Ulrich, I. Usherov, S. Wawoczny, M. Willers, M. W\"ustrich, and A. Z\"oller
Energy-Dependent Light Quenching in CaWO$_4$ Crystals at mK Temperatures
6 pages, 6 figures, 2 tables
Eur.Phys.J. C74 (2014) 2957
10.1140/epjc/s10052-014-2957-5
null
astro-ph.IM astro-ph.CO physics.ins-det
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Scintillating CaWO$_4$ single crystals are a promising multi-element target for rare-event searches and are currently used in the direct Dark Matter experiment CRESST (Cryogenic Rare Event Search with Superconducting Thermometers). The relative light output of different particle interactions in CaWO$_4$ is quantified by Quenching Factors (QFs). These are essential for an active background discrimination and the identification of a possible signal induced by weakly interacting massive particles (WIMPs). We present the first precise measurements of the QFs of O, Ca and W at mK temperatures by irradiating a cryogenic detector with a fast neutron beam. A clear energy dependence of the QF of O and, less pronounced, of Ca was observed for the first time. Furthermore, in CRESST neutron-calibration data a variation of the QFs among different CaWO$_4$ single crystals was found. For typical CRESST detectors the QFs in the region-of-interest (10-40$\,$keV) are $QF_O^{ROI}=(11.2{\pm}0.5)\,$%, $QF_{Ca}^{ROI}=(5.94{\pm}0.49)\,$% and $QF_W^{ROI}=(1.72{\pm}0.21)\,$%. The latest CRESST data (run32) is reanalyzed using these fundamentally new results on light quenching in CaWO$_4$ having moderate influence on the WIMP analysis. Their relevance for future CRESST runs and for the clarification of previously published results of direct Dark Matter experiments is emphasized.
[ { "created": "Tue, 14 Jan 2014 18:20:26 GMT", "version": "v1" }, { "created": "Mon, 25 Jan 2016 14:04:05 GMT", "version": "v2" } ]
2016-01-26
[ [ "Strauss", "R.", "" ], [ "Angloher", "G.", "" ], [ "Bento", "A.", "" ], [ "Bucci", "C.", "" ], [ "Canonica", "L.", "" ], [ "Carli", "W.", "" ], [ "Ciemniak", "C.", "" ], [ "Erb", "A.", "" ], [ "Feilitzsch", "F. v.", "" ], [ "Gorla", "P.", "" ], [ "Gütlein", "A.", "" ], [ "Hagn", "H.", "" ], [ "Hauff", "D.", "" ], [ "Hellgartner", "D.", "" ], [ "Jochum", "J.", "" ], [ "Kraus", "H.", "" ], [ "Lanfranchi", "J. -C.", "" ], [ "Loebell", "J.", "" ], [ "Münster", "A.", "" ], [ "Petricca", "F.", "" ], [ "Potzel", "W.", "" ], [ "Pröbst", "F.", "" ], [ "Reindl", "F.", "" ], [ "Roth", "S.", "" ], [ "Rottler", "K.", "" ], [ "Sailer", "C.", "" ], [ "Schäffner", "K.", "" ], [ "Schieck", "J.", "" ], [ "Scholl", "S.", "" ], [ "Schönert", "S.", "" ], [ "Seidel", "W.", "" ], [ "Sivers", "M. v.", "" ], [ "Stodolsky", "L.", "" ], [ "Strandhagen", "C.", "" ], [ "Tanzke", "A.", "" ], [ "Uffinger", "M.", "" ], [ "Ulrich", "A.", "" ], [ "Usherov", "I.", "" ], [ "Wawoczny", "S.", "" ], [ "Willers", "M.", "" ], [ "Wüstrich", "M.", "" ], [ "Zöller", "A.", "" ] ]
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1401.3351
Michael Wilczek
Michael Wilczek and Charles Meneveau
Pressure Hessian and viscous contributions to velocity gradient statistics based on Gaussian random fields
null
J. Fluid Mech. (2014), vol. 756, pp. 191-225
10.1017/jfm.2014.367
null
physics.flu-dyn
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Understanding the non-local pressure contributions and viscous effects on the small-scale statistics remains one of the central challenges in the study of homogeneous isotropic turbulence. Here we address this issue by studying the impact of the pressure Hessian as well as viscous diffusion on the statistics of the velocity gradient tensor in the framework of an exact statistical evolution equation. This evolution equation shares similarities with earlier phenomenological models for the Lagrangian velocity gradient tensor evolution, yet constitutes the starting point for a systematic study of the unclosed pressure Hessian and viscous diffusion terms. Based on the assumption of incompressible Gaussian velocity fields, closed expressions are obtained as the results of an evaluation of the characteristic functionals. The benefits and shortcomings of this Gaussian closure are discussed, and a generalization is proposed based on results from direct numerical simulations. This enhanced Gaussian closure yields, for example, insights on how the pressure Hessian prevents the finite-time singularity induced by the local self-amplification and how its interaction with viscous effects leads to the characteristic strain skewness phenomenon.
[ { "created": "Tue, 14 Jan 2014 21:03:44 GMT", "version": "v1" }, { "created": "Tue, 2 Sep 2014 08:33:17 GMT", "version": "v2" } ]
2014-09-03
[ [ "Wilczek", "Michael", "" ], [ "Meneveau", "Charles", "" ] ]
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1401.3365
Ling Xu
Ling Xu and Monika Nitsche
Numerical study of viscous starting flow past a flat plate
null
null
null
null
physics.flu-dyn
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Viscous flow past a finite plate which is impulsively started in direction normal to itself is studied numerically using a high order mixed finite difference and semi-Lagrangian scheme. The goal is to resolve details of the vorticity generation at early times, and to determine the effect of viscosity on flow quantities such as the core trajectory and vorticity, and the shed circulation. Vorticity contours, streaklines and streamlines are presented for a range of Reynolds numbers $Re \in [250, 2000]$ and a range of times $t \in[0. 0002, 5]$. At early times, most of the vorticity is attached to the plate. The paper proposes a definition for the shed circulation at early as well as late times, and shows that it indeed represents vorticity that separates from the plate without reattaching. The contribution of viscous diffusion to the circulation shedding rate is found to be significant, but, interestingly, to depend only slightly on the value of the Reynolds number. The shed circulation and the vortex core trajectories follow scaling laws for inviscid self-similar flow over several decades in time. Scaling laws describing the core vorticity, core dissipation, boundary layer thickness, drag and lift forces in time and Reynolds number are also presented. The simulations provide benchmark results to evaluate, for example, simpler separation models such as point vortex and vortex sheet models.
[ { "created": "Tue, 14 Jan 2014 21:37:38 GMT", "version": "v1" } ]
2014-01-16
[ [ "Xu", "Ling", "" ], [ "Nitsche", "Monika", "" ] ]
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1401.3372
Linas Vepstas PhD
Linas Vepstas and Ben Goertzel
Learning Language from a Large (Unannotated) Corpus
29 pages, 5 figures, research proposal
null
null
null
cs.CL cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A novel approach to the fully automated, unsupervised extraction of dependency grammars and associated syntax-to-semantic-relationship mappings from large text corpora is described. The suggested approach builds on the authors' prior work with the Link Grammar, RelEx and OpenCog systems, as well as on a number of prior papers and approaches from the statistical language learning literature. If successful, this approach would enable the mining of all the information needed to power a natural language comprehension and generation system, directly from a large, unannotated corpus.
[ { "created": "Tue, 14 Jan 2014 22:10:30 GMT", "version": "v1" } ]
2014-01-16
[ [ "Vepstas", "Linas", "" ], [ "Goertzel", "Ben", "" ] ]
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Learning Language from a Large (Unannotated) Corpus
http://arxiv.org/abs/1401.3372v1
http://arxiv.org/pdf/1401.3372v1.pdf
https://github.com/opencog/learn
false
false
https://paperswithcode.com/paper/learning-language-from-a-large-unannotated
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1401.3373
Ashraf Al Daoud
Ashraf Al Daoud (1), George Kesidis (2), J\"org Liebeherr (1) ((1) University of Toronto, (2) The Pennsylvania State University)
An Iterated Game of Uncoordinated Sharing of Licensed Spectrum Using Zero-Determinant Strategies
null
null
null
null
cs.GT cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider private commons for secondary sharing of licensed spectrum bands with no access coordination provided by the primary license holder. In such environments, heterogeneity in demand patterns of the secondary users can lead to constant changes in the interference levels, and thus can be a source of volatility to the utilities of the users. In this paper, we consider secondary users to be service providers that provide downlink services. We formulate the spectrum sharing problem as a non-cooperative iterated game of power control where service providers change their power levels to fix their long-term average rates at utility-maximizing values. First, we show that in any iterated 2x2 game, the structure of the single-stage game dictates the degree of control that a service provider can exert on the long-term outcome of the game. Then we show that if service providers use binary actions either to access or not to access the channel at any round of the game, then the long-term rate can be fixed regardless of the strategy of the opponent. We identify these rates and show that they can be achieved using mixed Markovian strategies that will be clearly identified in the paper.
[ { "created": "Tue, 14 Jan 2014 22:23:44 GMT", "version": "v1" } ]
2014-01-17
[ [ "Daoud", "Ashraf Al", "" ], [ "Kesidis", "George", "" ], [ "Liebeherr", "Jörg", "" ] ]
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1401.3374
Qiang Wang
Qiang Wang (1), Aswin J. Mathews (2), Ke Li (2), Jie Wen (2), Sergey Komarov (1), Joseph A. O'Sullivan (2) and Yuan-Chuan Tai (1) ((1) Department of Radiology, Washington University in St Louis, USA (2) Department of Electrical and Systems Engineering, Washington University, USA)
A dedicated high resolution PET imager for plant sciences
19 pages
2014 Phys. Med. Biol. 59 5613
10.1088/0031-9155/59/19/5613
null
physics.ins-det
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
PET provides in vivo molecular and functional imaging capability that is crucial to studying the interaction of plant with changing environment at the whole-plant level. We have developed a dedicated plant PET imager that features high spatial resolution, housed in a fully controlled environment provided by a plant growth chamber (PGC). The system currently contains two types of detector modules: 84 microPET R4 block detectors with 2.2 mm crystals to provide a large detecting area; and 32 Inveon block detectors with 1.5 mm crystals to provide higher spatial resolution. Outputs of the four microPET block detectors in a modular housing are concatenated by a custom printed circuit board to match the output characteristics of an Inveon detector. All the detectors are read out by QuickSilver electronics. The detector modules are configured to full rings with a 15 cm diameter trans-axial field of view (FOV) for dynamic tomographic imaging of small plants. Potentially, the Inveon detectors can be reconfigured to quarter-rings to get a 25 cm FOV using step-and-shoot motion. The imager contains 2 linear stages to position detectors at different heights for multi-bed scanning, and 2 rotation stages to collect coincidence events from all angles. The PET system has been built and integrated into the PGC. The system has a typical energy resolution of 15% for Inveon blocks and 24% for R4 blocks; timing resolution of 1.8 ns; and sensitivity of 1.3%,1.4%,3.0% measured at center of FOV, 5 cm off to R4 half-ring and 5 cm off to Inveon half-ring, respectively(with a 350-650 KeV energy and 3.1 ns timing window). System spatial resolution is similar to that of commercial microPET sytems, with 1.25 mm rod sources in the micro-Derenzo phantom resolved using ML-EM algorithm. Preliminary imaging experiments using different plants labeled with 11C-CO2 produced high-quality dynamic PET images.
[ { "created": "Tue, 14 Jan 2014 22:29:08 GMT", "version": "v1" } ]
2014-09-22
[ [ "Wang", "Qiang", "" ], [ "Mathews", "Aswin J.", "" ], [ "Li", "Ke", "" ], [ "Wen", "Jie", "" ], [ "Komarov", "Sergey", "" ], [ "O'Sullivan", "Joseph A.", "" ], [ "Tai", "Yuan-Chuan", "" ] ]
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1401.3375
Aly El Gamal
Aly El Gamal and Venugopal V. Veeravalli
Flexible Backhaul Design and Degrees of Freedom for Linear Interference Networks
Submitted to IEEE International Symposium on Information Theory (ISIT 2014)
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cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The considered problem is that of maximizing the degrees of freedom (DoF) in cellular downlink, under a backhaul load constraint that limits the number of messages that can be delivered from a centralized controller to the base station transmitters. A linear interference channel model is considered, where each transmitter is connected to the receiver having the same index as well as one succeeding receiver. The backhaul load is defined as the sum of all the messages available at all the transmitters normalized by the number of users. When the backhaul load is constrained to an integer level B, the asymptotic per user DoF is shown to equal (4B-1)/(4B), and it is shown that the optimal assignment of messages to transmitters is asymmetric and satisfies a local cooperation constraint and that the optimal coding scheme relies only on zero-forcing transmit beamforming. Finally, an extension of the presented coding scheme is shown to apply for more general locally connected and two-dimensional networks.
[ { "created": "Tue, 14 Jan 2014 22:30:23 GMT", "version": "v1" } ]
2014-01-16
[ [ "Gamal", "Aly El", "" ], [ "Veeravalli", "Venugopal V.", "" ] ]
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1401.3376
Guohua Wu
Guohua Wu
Across neighbourhood search for numerical optimization
null
Guohua Wu , Across neighbourhood search for numerical optimization, Information Sciences (2015), doi: 10.1016/j.ins.2015.09.051
10.1016/j.ins.2015.09.051
null
cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Population-based search algorithms (PBSAs), including swarm intelligence algorithms (SIAs) and evolutionary algorithms (EAs), are competitive alternatives for solving complex optimization problems and they have been widely applied to real-world optimization problems in different fields. In this study, a novel population-based across neighbourhood search (ANS) is proposed for numerical optimization. ANS is motivated by two straightforward assumptions and three important issues raised in improving and designing efficient PBSAs. In ANS, a group of individuals collaboratively search the solution space for an optimal solution of the optimization problem considered. A collection of superior solutions found by individuals so far is maintained and updated dynamically. At each generation, an individual directly searches across the neighbourhoods of multiple superior solutions with the guidance of a Gaussian distribution. This search manner is referred to as across neighbourhood search. The characteristics of ANS are discussed and the concept comparisons with other PBSAs are given. The principle behind ANS is simple. Moreover, ANS is easy for implementation and application with three parameters being required to tune. Extensive experiments on 18 benchmark optimization functions of different types show that ANS has well balanced exploration and exploitation capabilities and performs competitively compared with many efficient PBSAs (Related Matlab codes used in the experiments are available from http://guohuawunudt.gotoip2.com/publications.html).
[ { "created": "Tue, 14 Jan 2014 22:35:48 GMT", "version": "v1" }, { "created": "Tue, 30 Dec 2014 12:20:04 GMT", "version": "v2" }, { "created": "Mon, 19 Oct 2015 16:21:24 GMT", "version": "v3" } ]
2015-10-20
[ [ "Wu", "Guohua", "" ] ]
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1401.3381
Jan Bergstra
Jan A. Bergstra and Mark Burgess
Promises, Impositions, and other Directionals
55 pages
null
null
null
cs.MA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Promises, impositions, proposals, predictions, and suggestions are categorized as voluntary co-operational methods. The class of voluntary co-operational methods is included in the class of so-called directionals. Directionals are mechanisms supporting the mutual coordination of autonomous agents. Notations are provided capable of expressing residual fragments of directionals. An extensive example, involving promises about the suitability of programs for tasks imposed on the promisee is presented. The example illustrates the dynamics of promises and more specifically the corresponding mechanism of trust updating and credibility updating. Trust levels and credibility levels then determine the way certain promises and impositions are handled. The ubiquity of promises and impositions is further demonstrated with two extensive examples involving human behaviour: an artificial example about an agent planning a purchase, and a realistic example describing technology mediated interaction concerning the solution of pay station failure related problems arising for an agent intending to leave the parking area.
[ { "created": "Tue, 14 Jan 2014 22:55:11 GMT", "version": "v1" } ]
2014-01-16
[ [ "Bergstra", "Jan A.", "" ], [ "Burgess", "Mark", "" ] ]
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1401.3385
Val\'erio Ramos Batista
Antonio Elias Fabris and Val\'erio Ramos Batista
A programme to determine the exact interior of any connected digital picture
null
null
null
null
cs.CG cs.CV cs.GR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Region filling is one of the most important and fundamental operations in computer graphics and image processing. Many filling algorithms and their implementations are based on the Euclidean geometry, which are then translated into computational models moving carelessly from the continuous to the finite discrete space of the computer. The consequences of this approach is that most implementations fail when tested for challenging degenerate and nearly degenerate regions. We present a correct integer-only procedure that works for all connected digital pictures. It finds all possible interior points, which are then displayed and stored in a locating matrix. Namely, we present a filling and locating procedure that can be used in computer graphics and image processing applications.
[ { "created": "Tue, 14 Jan 2014 23:21:58 GMT", "version": "v1" } ]
2014-01-16
[ [ "Fabris", "Antonio Elias", "" ], [ "Batista", "Valério Ramos", "" ] ]
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1401.3387
Ahmed El Shafie
Ahmed El Shafie and Tamer Khattab and H. Vincent Poor
Maximum Throughput of a Cooperative Energy Harvesting Cognitive Radio User
Part of this paper was accepted for publication in PIMRC 2014
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null
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cs.IT cs.NI math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we investigate the maximum throughput of a saturated rechargeable secondary user (SU) sharing the spectrum with a primary user (PU). The SU harvests energy packets (tokens) from the environment with a certain harvesting rate. All transmitters are assumed to have data buffers to store the incoming data packets. In addition to its own traffic buffer, the SU has a buffer for storing the admitted primary packets for relaying; and a buffer for storing the energy tokens harvested from the environment. We propose a new cooperative cognitive relaying protocol that allows the SU to relay a fraction of the undelivered primary packets. We consider an interference channel model (or a multipacket reception (MPR) channel model), where concurrent transmissions can survive from interference with certain probability characterized by the complement of channel outages. The proposed protocol exploits the primary queue burstiness and receivers' MPR capability. In addition, it efficiently expends the secondary energy tokens under the objective of secondary throughput maximization. Our numerical results show the benefits of cooperation, receivers' MPR capability, and secondary energy queue arrival rate on the system performance from a network layer standpoint.
[ { "created": "Tue, 14 Jan 2014 23:38:07 GMT", "version": "v1" }, { "created": "Tue, 10 Jun 2014 18:51:51 GMT", "version": "v2" }, { "created": "Tue, 8 Jul 2014 21:14:50 GMT", "version": "v3" } ]
2014-07-10
[ [ "Shafie", "Ahmed El", "" ], [ "Khattab", "Tamer", "" ], [ "Poor", "H. Vincent", "" ] ]
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1401.3390
Mahdi Pakdaman Naeini
Mahdi Pakdaman Naeini, Gregory F. Cooper, Milos Hauskrecht
Binary Classifier Calibration: Non-parametric approach
null
null
null
null
stat.ML cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Accurate calibration of probabilistic predictive models learned is critical for many practical prediction and decision-making tasks. There are two main categories of methods for building calibrated classifiers. One approach is to develop methods for learning probabilistic models that are well-calibrated, ab initio. The other approach is to use some post-processing methods for transforming the output of a classifier to be well calibrated, as for example histogram binning, Platt scaling, and isotonic regression. One advantage of the post-processing approach is that it can be applied to any existing probabilistic classification model that was constructed using any machine-learning method. In this paper, we first introduce two measures for evaluating how well a classifier is calibrated. We prove three theorems showing that using a simple histogram binning post-processing method, it is possible to make a classifier be well calibrated while retaining its discrimination capability. Also, by casting the histogram binning method as a density-based non-parametric binary classifier, we can extend it using two simple non-parametric density estimation methods. We demonstrate the performance of the proposed calibration methods on synthetic and real datasets. Experimental results show that the proposed methods either outperform or are comparable to existing calibration methods.
[ { "created": "Tue, 14 Jan 2014 23:52:16 GMT", "version": "v1" } ]
2014-01-16
[ [ "Naeini", "Mahdi Pakdaman", "" ], [ "Cooper", "Gregory F.", "" ], [ "Hauskrecht", "Milos", "" ] ]
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1401.3404
Wei Li
Cheng Lv, Wei Li, Xunya Jiang, Juncheng Cao
Far-field super-resolution imaging with a planar hyperbolic metamaterial lens beyond the Fabry-Perot resonance condition
Europhys. Lett. 2014
null
null
null
physics.optics cond-mat.mes-hall
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We demonstrate achieving the far-field super-resolution imaging can be realized by using a planar hyperbolic metamaterial lens (PHML), beyond the Fabry-Perot resonance condition. Although the thickness of the PHML is much larger than wavelength, the PHML not only can transmit radiative waves and evanescent waves with high transmission, but also can collect all the waves in the image region with the amplitudes of them being the same order of magnitude. We present a design for a PHML to realize the far-field super-resolution imaging, with the distance between the sources and the images 10 times larger than wavelength. We show the superresolution of our PHML is robust against losses, and the PHML can be fabricated by periodic stacking of metal and dielectric layers.
[ { "created": "Wed, 15 Jan 2014 01:41:01 GMT", "version": "v1" } ]
2014-01-16
[ [ "Lv", "Cheng", "" ], [ "Li", "Wei", "" ], [ "Jiang", "Xunya", "" ], [ "Cao", "Juncheng", "" ] ]
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1401.3409
Xiaowei Zhou
Xiaowei Zhou, Can Yang, Hongyu Zhao, Weichuan Yu
Low-Rank Modeling and Its Applications in Image Analysis
To appear in ACM Computing Surveys
null
null
null
cs.CV cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Low-rank modeling generally refers to a class of methods that solve problems by representing variables of interest as low-rank matrices. It has achieved great success in various fields including computer vision, data mining, signal processing and bioinformatics. Recently, much progress has been made in theories, algorithms and applications of low-rank modeling, such as exact low-rank matrix recovery via convex programming and matrix completion applied to collaborative filtering. These advances have brought more and more attentions to this topic. In this paper, we review the recent advance of low-rank modeling, the state-of-the-art algorithms, and related applications in image analysis. We first give an overview to the concept of low-rank modeling and challenging problems in this area. Then, we summarize the models and algorithms for low-rank matrix recovery and illustrate their advantages and limitations with numerical experiments. Next, we introduce a few applications of low-rank modeling in the context of image analysis. Finally, we conclude this paper with some discussions.
[ { "created": "Wed, 15 Jan 2014 02:17:33 GMT", "version": "v1" }, { "created": "Tue, 10 Jun 2014 03:40:29 GMT", "version": "v2" }, { "created": "Thu, 23 Oct 2014 02:05:18 GMT", "version": "v3" } ]
2014-10-24
[ [ "Zhou", "Xiaowei", "" ], [ "Yang", "Can", "" ], [ "Zhao", "Hongyu", "" ], [ "Yu", "Weichuan", "" ] ]
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1401.3410
Huseyin Birkan Yilmaz
H. Birkan Yilmaz, Na-Rae Kim, Chan-Byoung Chae
Effect of ISI Mitigation on Modulation Techniques in Communication via Diffusion
9 pages, 10 figures, 27 references, conference, two-column format
null
null
null
cs.ET cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Communication via diffusion (CvD) is an effective and energy efficient method for transmitting information in nanonetworks. In this work, we focus on a diffusion-based communication system where the reception process is an absorption via receptors. Whenever a molecule hits to the receiver it is removed from the environment. This kind of reception process is called first passage process and it is more complicated compared to diffusion process only. In 3-D environments, obtaining analytical solution for hitting time distribution for realistic cases is complicated, hence we develop an end-to-end simulator for he diffusion-based communication system that sends consecutive symbols. In CvD, each symbol is modulated and demodulated in a time slot called symbol duration, however the long tail distribution of hitting time is the main challenge that affects the symbol detection error. The molecules arriving in the following slots become an interference source when detection takes place. End-to-end simulator enables us to analyze the effect of inter symbol interference (ISI) without making any assumptions on the ISI. We propose an ISI cancellation technique that utilizes decision feedback for compensating the effect of previously demodulated symbol. Three different modulation types are considered with pulse, square, and cosine carrier waves. In case of constraints on transmitter or receiver node it may not be possible to use pulse as a carrier, and peak-to-average messenger molecule metric is defined for this purpose. Results show that, the proposed ISI mitigation technique improves the symbol detection performance and the amplitude-based modulations are improved more than frequency-based modulations.
[ { "created": "Wed, 15 Jan 2014 02:26:23 GMT", "version": "v1" } ]
2014-01-16
[ [ "Yilmaz", "H. Birkan", "" ], [ "Kim", "Na-Rae", "" ], [ "Chae", "Chan-Byoung", "" ] ]
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1401.3413
Avneesh Saluja
Avneesh Saluja, Mahdi Pakdaman, Dongzhen Piao, Ankur P. Parikh
Infinite Mixed Membership Matrix Factorization
For ICDM 2013 Workshop Proceedings
null
null
null
cs.LG cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Rating and recommendation systems have become a popular application area for applying a suite of machine learning techniques. Current approaches rely primarily on probabilistic interpretations and extensions of matrix factorization, which factorizes a user-item ratings matrix into latent user and item vectors. Most of these methods fail to model significant variations in item ratings from otherwise similar users, a phenomenon known as the "Napoleon Dynamite" effect. Recent efforts have addressed this problem by adding a contextual bias term to the rating, which captures the mood under which a user rates an item or the context in which an item is rated by a user. In this work, we extend this model in a nonparametric sense by learning the optimal number of moods or contexts from the data, and derive Gibbs sampling inference procedures for our model. We evaluate our approach on the MovieLens 1M dataset, and show significant improvements over the optimal parametric baseline, more than twice the improvements previously encountered for this task. We also extract and evaluate a DBLP dataset, wherein we predict the number of papers co-authored by two authors, and present improvements over the parametric baseline on this alternative domain as well.
[ { "created": "Wed, 15 Jan 2014 02:39:15 GMT", "version": "v1" } ]
2014-01-16
[ [ "Saluja", "Avneesh", "" ], [ "Pakdaman", "Mahdi", "" ], [ "Piao", "Dongzhen", "" ], [ "Parikh", "Ankur P.", "" ] ]
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1401.3417
Amarendra Kumar Sarma Dr.
Pawan Kumar and Amarendra K. Sarma
Coherent manipulation of four-level double lambda-like atomic system by a train of ultra-short few-cycle-optical pulses
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null
null
physics.optics physics.atom-ph quant-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We have demonstrated that near complete coherence can be achieved in a four level double lambda-like systems using a train of ultra-short optical pulses. The effect of the Doppler broadening has been analyzed and a scheme has been proposed for establishing high and uniform coherence across different velocity groups in the atomic ensemble. We have also presented a novel scheme of excitation using chirped pulses and shown that in addition to generating coherence in the system it is possible to alter the translational states of the atoms.
[ { "created": "Wed, 15 Jan 2014 03:00:35 GMT", "version": "v1" } ]
2014-01-16
[ [ "Kumar", "Pawan", "" ], [ "Sarma", "Amarendra K.", "" ] ]
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1401.3420
Christoph Studer
Christoph Studer, Tom Goldstein, Wotao Yin, Richard G. Baraniuk
Democratic Representations
Submitted to a Journal
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Minimization of the $\ell_{\infty}$ (or maximum) norm subject to a constraint that imposes consistency to an underdetermined system of linear equations finds use in a large number of practical applications, including vector quantization, approximate nearest neighbor search, peak-to-average power ratio (or "crest factor") reduction in communication systems, and peak force minimization in robotics and control. This paper analyzes the fundamental properties of signal representations obtained by solving such a convex optimization problem. We develop bounds on the maximum magnitude of such representations using the uncertainty principle (UP) introduced by Lyubarskii and Vershynin, and study the efficacy of $\ell_{\infty}$-norm-based dynamic range reduction. Our analysis shows that matrices satisfying the UP, such as randomly subsampled Fourier or i.i.d. Gaussian matrices, enable the computation of what we call democratic representations, whose entries all have small and similar magnitude, as well as low dynamic range. To compute democratic representations at low computational complexity, we present two new, efficient convex optimization algorithms. We finally demonstrate the efficacy of democratic representations for dynamic range reduction in a DVB-T2-based broadcast system.
[ { "created": "Wed, 15 Jan 2014 03:24:38 GMT", "version": "v1" }, { "created": "Tue, 21 Apr 2015 16:47:30 GMT", "version": "v2" } ]
2015-04-22
[ [ "Studer", "Christoph", "" ], [ "Goldstein", "Tom", "" ], [ "Yin", "Wotao", "" ], [ "Baraniuk", "Richard G.", "" ] ]
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1401.3421
Rourab Paul
Sruti Agarwal, Sangeet Saha, Rourab Paul, Amlan Chakrabarti
Performance Evaluation of ECC in Single and Multi Processor Architectures on FPGA Based Embedded System
Published Book Title: Elsevier Science and Technology, ICCN 2013, Bangalore, Page(s): 140 - 147, Volume 3, 03.elsevierst.2013.3.ICCN16, ISBN :9789351071044, Paper link:-http://searchdl.org/index.php/book_series/view/917
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cs.AR cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Cryptographic algorithms are computationally costly and the challenge is more if we need to execute them in resource constrained embedded systems. Field Programmable Gate Arrays (FPGAs) having programmable logic de- vices and processing cores, have proven to be highly feasible implementation platforms for embedded systems providing lesser design time and reconfig- urability. Design parameters like throughput, resource utilization and power requirements are the key issues. The popular Elliptic Curve Cryptography (ECC), which is superior over other public-key crypto-systems like RSA in many ways, such as providing greater security for a smaller key size, is cho- sen in this work and the possibilities of its implementation in FPGA based embedded systems for both single and dual processor core architectures in- volving task parallelization have been explored. This exploration, which is first of its kind considering the other existing works, is a needed activity for evaluating the best possible architectural environment for ECC implementa- tion on FPGA (Virtex4 XC4VFX12, FF668, -10) based embedded platform.
[ { "created": "Wed, 15 Jan 2014 03:25:41 GMT", "version": "v1" } ]
2014-02-20
[ [ "Agarwal", "Sruti", "" ], [ "Saha", "Sangeet", "" ], [ "Paul", "Rourab", "" ], [ "Chakrabarti", "Amlan", "" ] ]
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1401.3426
Ya'akov Gal
Yaakov Gal, Avi Pfeffer
Networks of Influence Diagrams: A Formalism for Representing Agents' Beliefs and Decision-Making Processes
null
Journal Of Artificial Intelligence Research, Volume 33, pages 109-147, 2008
10.1613/jair.2503
null
cs.GT cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents Networks of Influence Diagrams (NID), a compact, natural and highly expressive language for reasoning about agents beliefs and decision-making processes. NIDs are graphical structures in which agents mental models are represented as nodes in a network; a mental model for an agent may itself use descriptions of the mental models of other agents. NIDs are demonstrated by examples, showing how they can be used to describe conflicting and cyclic belief structures, and certain forms of bounded rationality. In an opponent modeling domain, NIDs were able to outperform other computational agents whose strategies were not known in advance. NIDs are equivalent in representation to Bayesian games but they are more compact and structured than this formalism. In particular, the equilibrium definition for NIDs makes an explicit distinction between agents optimal strategies, and how they actually behave in reality.
[ { "created": "Wed, 15 Jan 2014 04:38:59 GMT", "version": "v1" } ]
2014-01-16
[ [ "Gal", "Yaakov", "" ], [ "Pfeffer", "Avi", "" ] ]
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1401.3427
Laurent Miclet
Laurent Miclet, Sabri Bayoudh, Arnaud Delhay
Analogical Dissimilarity: Definition, Algorithms and Two Experiments in Machine Learning
null
Journal Of Artificial Intelligence Research, Volume 32, pages 793-824, 2008
10.1613/jair.2519
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper defines the notion of analogical dissimilarity between four objects, with a special focus on objects structured as sequences. Firstly, it studies the case where the four objects have a null analogical dissimilarity, i.e. are in analogical proportion. Secondly, when one of these objects is unknown, it gives algorithms to compute it. Thirdly, it tackles the problem of defining analogical dissimilarity, which is a measure of how far four objects are from being in analogical proportion. In particular, when objects are sequences, it gives a definition and an algorithm based on an optimal alignment of the four sequences. It gives also learning algorithms, i.e. methods to find the triple of objects in a learning sample which has the least analogical dissimilarity with a given object. Two practical experiments are described: the first is a classification problem on benchmarks of binary and nominal data, the second shows how the generation of sequences by solving analogical equations enables a handwritten character recognition system to rapidly be adapted to a new writer.
[ { "created": "Wed, 15 Jan 2014 04:42:13 GMT", "version": "v1" } ]
2014-01-16
[ [ "Miclet", "Laurent", "" ], [ "Bayoudh", "Sabri", "" ], [ "Delhay", "Arnaud", "" ] ]
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1401.3428
Nicolas Meuleau
Nicolas Meuleau, Emmanuel Benazera, Ronen I. Brafman, Eric A. Hansen, Mausam
A Heuristic Search Approach to Planning with Continuous Resources in Stochastic Domains
null
Journal Of Artificial Intelligence Research, Volume 34, pages 27-59, 2009
10.1613/jair.2529
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the problem of optimal planning in stochastic domains with resource constraints, where the resources are continuous and the choice of action at each step depends on resource availability. We introduce the HAO* algorithm, a generalization of the AO* algorithm that performs search in a hybrid state space that is modeled using both discrete and continuous state variables, where the continuous variables represent monotonic resources. Like other heuristic search algorithms, HAO* leverages knowledge of the start state and an admissible heuristic to focus computational effort on those parts of the state space that could be reached from the start state by following an optimal policy. We show that this approach is especially effective when resource constraints limit how much of the state space is reachable. Experimental results demonstrate its effectiveness in the domain that motivates our research: automated planning for planetary exploration rovers.
[ { "created": "Wed, 15 Jan 2014 04:46:00 GMT", "version": "v1" } ]
2014-01-16
[ [ "Meuleau", "Nicolas", "" ], [ "Benazera", "Emmanuel", "" ], [ "Brafman", "Ronen I.", "" ], [ "Hansen", "Eric A.", "" ], [ "Mausam", "", "" ] ]
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1401.3429
Yi Wang
Yi Wang, Nevin L. Zhang, Tao Chen
Latent Tree Models and Approximate Inference in Bayesian Networks
null
Journal Of Artificial Intelligence Research, Volume 32, pages 879-900, 2008
10.1613/jair.2530
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose a novel method for approximate inference in Bayesian networks (BNs). The idea is to sample data from a BN, learn a latent tree model (LTM) from the data offline, and when online, make inference with the LTM instead of the original BN. Because LTMs are tree-structured, inference takes linear time. In the meantime, they can represent complex relationship among leaf nodes and hence the approximation accuracy is often good. Empirical evidence shows that our method can achieve good approximation accuracy at low online computational cost.
[ { "created": "Wed, 15 Jan 2014 04:46:37 GMT", "version": "v1" } ]
2014-01-16
[ [ "Wang", "Yi", "" ], [ "Zhang", "Nevin L.", "" ], [ "Chen", "Tao", "" ] ]
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1401.3430
Lucas Bordeaux
Lucas Bordeaux, Marco Cadoli, Toni Mancini
A Unifying Framework for Structural Properties of CSPs: Definitions, Complexity, Tractability
null
Journal Of Artificial Intelligence Research, Volume 32, pages 607-629, 2008
10.1613/jair.2538
null
cs.AI cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Literature on Constraint Satisfaction exhibits the definition of several structural properties that can be possessed by CSPs, like (in)consistency, substitutability or interchangeability. Current tools for constraint solving typically detect such properties efficiently by means of incomplete yet effective algorithms, and use them to reduce the search space and boost search. In this paper, we provide a unifying framework encompassing most of the properties known so far, both in CSP and other fields literature, and shed light on the semantical relationships among them. This gives a unified and comprehensive view of the topic, allows new, unknown, properties to emerge, and clarifies the computational complexity of the various detection problems. In particular, among the others, two new concepts, fixability and removability emerge, that come out to be the ideal characterisations of values that may be safely assigned or removed from a variables domain, while preserving problem satisfiability. These two notions subsume a large number of known properties, including inconsistency, substitutability and others. Because of the computational intractability of all the property-detection problems, by following the CSP approach we then determine a number of relaxations which provide sufficient conditions for their tractability. In particular, we exploit forms of language restrictions and local reasoning.
[ { "created": "Wed, 15 Jan 2014 04:47:30 GMT", "version": "v1" } ]
2014-01-16
[ [ "Bordeaux", "Lucas", "" ], [ "Cadoli", "Marco", "" ], [ "Mancini", "Toni", "" ] ]
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1401.3431
James Delgrande
James Delgrande, Yi Jin, Francis Jeffry Pelletier
Compositional Belief Update
null
Journal Of Artificial Intelligence Research, Volume 32, pages 757-791, 2008
10.1613/jair.2539
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we explore a class of belief update operators, in which the definition of the operator is compositional with respect to the sentence to be added. The goal is to provide an update operator that is intuitive, in that its definition is based on a recursive decomposition of the update sentences structure, and that may be reasonably implemented. In addressing update, we first provide a definition phrased in terms of the models of a knowledge base. While this operator satisfies a core group of the benchmark Katsuno-Mendelzon update postulates, not all of the postulates are satisfied. Other Katsuno-Mendelzon postulates can be obtained by suitably restricting the syntactic form of the sentence for update, as we show. In restricting the syntactic form of the sentence for update, we also obtain a hierarchy of update operators with Winsletts standard semantics as the most basic interesting approach captured. We subsequently give an algorithm which captures this approach; in the general case the algorithm is exponential, but with some not-unreasonable assumptions we obtain an algorithm that is linear in the size of the knowledge base. Hence the resulting approach has much better complexity characteristics than other operators in some situations. We also explore other compositional belief change operators: erasure is developed as a dual operator to update; we show that a forget operator is definable in terms of update; and we give a definition of the compositional revision operator. We obtain that compositional revision, under the most natural definition, yields the Satoh revision operator.
[ { "created": "Wed, 15 Jan 2014 04:48:21 GMT", "version": "v1" } ]
2014-01-16
[ [ "Delgrande", "James", "" ], [ "Jin", "Yi", "" ], [ "Pelletier", "Francis Jeffry", "" ] ]
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1401.3432
Tinne De Laet
Tinne De Laet, Joris De Schutter, Herman Bruyninckx
A Rigorously Bayesian Beam Model and an Adaptive Full Scan Model for Range Finders in Dynamic Environments
null
Journal Of Artificial Intelligence Research, Volume 33, pages 179-222, 2008
10.1613/jair.2540
null
cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper proposes and experimentally validates a Bayesian network model of a range finder adapted to dynamic environments. All modeling assumptions are rigorously explained, and all model parameters have a physical interpretation. This approach results in a transparent and intuitive model. With respect to the state of the art beam model this paper: (i) proposes a different functional form for the probability of range measurements caused by unmodeled objects, (ii) intuitively explains the discontinuity encountered in te state of the art beam model, and (iii) reduces the number of model parameters, while maintaining the same representational power for experimental data. The proposed beam model is called RBBM, short for Rigorously Bayesian Beam Model. A maximum likelihood and a variational Bayesian estimator (both based on expectation-maximization) are proposed to learn the model parameters. Furthermore, the RBBM is extended to a full scan model in two steps: first, to a full scan model for static environments and next, to a full scan model for general, dynamic environments. The full scan model accounts for the dependency between beams and adapts to the local sample density when using a particle filter. In contrast to Gaussian-based state of the art models, the proposed full scan model uses a sample-based approximation. This sample-based approximation enables handling dynamic environments and capturing multi-modality, which occurs even in simple static environments.
[ { "created": "Wed, 15 Jan 2014 04:49:23 GMT", "version": "v1" } ]
2014-01-16
[ [ "De Laet", "Tinne", "" ], [ "De Schutter", "Joris", "" ], [ "Bruyninckx", "Herman", "" ] ]
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1401.3433
Enrico H. Gerding
Enrico H. Gerding, Rajdeep Kumar Dash, Andrew Byde, Nicholas Robert Jennings
Optimal Strategies for Simultaneous Vickrey Auctions with Perfect Substitutes
null
Journal Of Artificial Intelligence Research, Volume 32, pages 939-982, 2008
10.1613/jair.2544
null
cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We derive optimal strategies for a bidding agent that participates in multiple, simultaneous second-price auctions with perfect substitutes. We prove that, if everyone else bids locally in a single auction, the global bidder should always place non-zero bids in all available auctions, provided there are no budget constraints. With a budget, however, the optimal strategy is to bid locally if this budget is equal or less than the valuation. Furthermore, for a wide range of valuation distributions, we prove that the problem of finding the optimal bids reduces to two dimensions if all auctions are identical. Finally, we address markets with both sequential and simultaneous auctions, non-identical auctions, and the allocative efficiency of the market.
[ { "created": "Wed, 15 Jan 2014 04:50:20 GMT", "version": "v1" } ]
2014-01-16
[ [ "Gerding", "Enrico H.", "" ], [ "Dash", "Rajdeep Kumar", "" ], [ "Byde", "Andrew", "" ], [ "Jennings", "Nicholas Robert", "" ] ]
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1401.3434
Bal\'azs Csan\'ad Cs\'aji
Bal\'azs Csan\'ad Cs\'aji, L\'aszl\'o Monostori
Adaptive Stochastic Resource Control: A Machine Learning Approach
null
Journal Of Artificial Intelligence Research, Volume 32, pages 453-486, 2008
10.1613/jair.2548
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The paper investigates stochastic resource allocation problems with scarce, reusable resources and non-preemtive, time-dependent, interconnected tasks. This approach is a natural generalization of several standard resource management problems, such as scheduling and transportation problems. First, reactive solutions are considered and defined as control policies of suitably reformulated Markov decision processes (MDPs). We argue that this reformulation has several favorable properties, such as it has finite state and action spaces, it is aperiodic, hence all policies are proper and the space of control policies can be safely restricted. Next, approximate dynamic programming (ADP) methods, such as fitted Q-learning, are suggested for computing an efficient control policy. In order to compactly maintain the cost-to-go function, two representations are studied: hash tables and support vector regression (SVR), particularly, nu-SVRs. Several additional improvements, such as the application of limited-lookahead rollout algorithms in the initial phases, action space decomposition, task clustering and distributed sampling are investigated, too. Finally, experimental results on both benchmark and industry-related data are presented.
[ { "created": "Wed, 15 Jan 2014 04:50:50 GMT", "version": "v1" } ]
2014-01-16
[ [ "Csáji", "Balázs Csanád", "" ], [ "Monostori", "László", "" ] ]
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1401.3436
St\'ephane Ross
St\'ephane Ross, Joelle Pineau, S\'ebastien Paquet, Brahim Chaib-draa
Online Planning Algorithms for POMDPs
null
Journal Of Artificial Intelligence Research, Volume 32, pages 663-704, 2008
10.1613/jair.2567
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Partially Observable Markov Decision Processes (POMDPs) provide a rich framework for sequential decision-making under uncertainty in stochastic domains. However, solving a POMDP is often intractable except for small problems due to their complexity. Here, we focus on online approaches that alleviate the computational complexity by computing good local policies at each decision step during the execution. Online algorithms generally consist of a lookahead search to find the best action to execute at each time step in an environment. Our objectives here are to survey the various existing online POMDP methods, analyze their properties and discuss their advantages and disadvantages; and to thoroughly evaluate these online approaches in different environments under various metrics (return, error bound reduction, lower bound improvement). Our experimental results indicate that state-of-the-art online heuristic search methods can handle large POMDP domains efficiently.
[ { "created": "Wed, 15 Jan 2014 04:52:25 GMT", "version": "v1" } ]
2014-01-16
[ [ "Ross", "Stéphane", "" ], [ "Pineau", "Joelle", "" ], [ "Paquet", "Sébastien", "" ], [ "Chaib-draa", "Brahim", "" ] ]
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1401.3437
Eyal Amir
Eyal Amir, Allen Chang
Learning Partially Observable Deterministic Action Models
null
Journal Of Artificial Intelligence Research, Volume 33, pages 349-402, 2008
10.1613/jair.2575
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present exact algorithms for identifying deterministic-actions effects and preconditions in dynamic partially observable domains. They apply when one does not know the action model(the way actions affect the world) of a domain and must learn it from partial observations over time. Such scenarios are common in real world applications. They are challenging for AI tasks because traditional domain structures that underly tractability (e.g., conditional independence) fail there (e.g., world features become correlated). Our work departs from traditional assumptions about partial observations and action models. In particular, it focuses on problems in which actions are deterministic of simple logical structure and observation models have all features observed with some frequency. We yield tractable algorithms for the modified problem for such domains. Our algorithms take sequences of partial observations over time as input, and output deterministic action models that could have lead to those observations. The algorithms output all or one of those models (depending on our choice), and are exact in that no model is misclassified given the observations. Our algorithms take polynomial time in the number of time steps and state features for some traditional action classes examined in the AI-planning literature, e.g., STRIPS actions. In contrast, traditional approaches for HMMs and Reinforcement Learning are inexact and exponentially intractable for such domains. Our experiments verify the theoretical tractability guarantees, and show that we identify action models exactly. Several applications in planning, autonomous exploration, and adventure-game playing already use these results. They are also promising for probabilistic settings, partially observable reinforcement learning, and diagnosis.
[ { "created": "Wed, 15 Jan 2014 04:52:56 GMT", "version": "v1" } ]
2014-01-16
[ [ "Amir", "Eyal", "" ], [ "Chang", "Allen", "" ] ]
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1401.3438
Neil C.A. Moore
Neil C.A. Moore, Patrick Prosser
The Ultrametric Constraint and its Application to Phylogenetics
null
Journal Of Artificial Intelligence Research, Volume 32, pages 901-938, 2008
10.1613/jair.2580
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A phylogenetic tree shows the evolutionary relationships among species. Internal nodes of the tree represent speciation events and leaf nodes correspond to species. A goal of phylogenetics is to combine such trees into larger trees, called supertrees, whilst respecting the relationships in the original trees. A rooted tree exhibits an ultrametric property; that is, for any three leaves of the tree it must be that one pair has a deeper most recent common ancestor than the other pairs, or that all three have the same most recent common ancestor. This inspires a constraint programming encoding for rooted trees. We present an efficient constraint that enforces the ultrametric property over a symmetric array of constrained integer variables, with the inevitable property that the lower bounds of any three variables are mutually supportive. We show that this allows an efficient constraint-based solution to the supertree construction problem. We demonstrate that the versatility of constraint programming can be exploited to allow solutions to variants of the supertree construction problem.
[ { "created": "Wed, 15 Jan 2014 04:53:22 GMT", "version": "v1" } ]
2014-01-16
[ [ "Moore", "Neil C. A.", "" ], [ "Prosser", "Patrick", "" ] ]
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1401.3439
Sonia Chernova
Sonia Chernova, Manuela Veloso
Interactive Policy Learning through Confidence-Based Autonomy
null
Journal Of Artificial Intelligence Research, Volume 34, pages 1-25, 2009
10.1613/jair.2584
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present Confidence-Based Autonomy (CBA), an interactive algorithm for policy learning from demonstration. The CBA algorithm consists of two components which take advantage of the complimentary abilities of humans and computer agents. The first component, Confident Execution, enables the agent to identify states in which demonstration is required, to request a demonstration from the human teacher and to learn a policy based on the acquired data. The algorithm selects demonstrations based on a measure of action selection confidence, and our results show that using Confident Execution the agent requires fewer demonstrations to learn the policy than when demonstrations are selected by a human teacher. The second algorithmic component, Corrective Demonstration, enables the teacher to correct any mistakes made by the agent through additional demonstrations in order to improve the policy and future task performance. CBA and its individual components are compared and evaluated in a complex simulated driving domain. The complete CBA algorithm results in the best overall learning performance, successfully reproducing the behavior of the teacher while balancing the tradeoff between number of demonstrations and number of incorrect actions during learning.
[ { "created": "Wed, 15 Jan 2014 04:53:48 GMT", "version": "v1" } ]
2014-01-16
[ [ "Chernova", "Sonia", "" ], [ "Veloso", "Manuela", "" ] ]
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1401.3441
Ran El-Yaniv
Ran El-Yaniv, Dmitry Pechyony
Transductive Rademacher Complexity and its Applications
null
Journal Of Artificial Intelligence Research, Volume 35, pages 193-234, 2009
10.1613/jair.2587
null
cs.LG cs.AI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We develop a technique for deriving data-dependent error bounds for transductive learning algorithms based on transductive Rademacher complexity. Our technique is based on a novel general error bound for transduction in terms of transductive Rademacher complexity, together with a novel bounding technique for Rademacher averages for particular algorithms, in terms of their "unlabeled-labeled" representation. This technique is relevant to many advanced graph-based transductive algorithms and we demonstrate its effectiveness by deriving error bounds to three well known algorithms. Finally, we present a new PAC-Bayesian bound for mixtures of transductive algorithms based on our Rademacher bounds.
[ { "created": "Wed, 15 Jan 2014 04:54:14 GMT", "version": "v1" } ]
2014-01-16
[ [ "El-Yaniv", "Ran", "" ], [ "Pechyony", "Dmitry", "" ] ]
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1401.3442
Amir Gershman
Amir Gershman, Amnon Meisels, Roie Zivan
Asynchronous Forward Bounding for Distributed COPs
null
Journal Of Artificial Intelligence Research, Volume 34, pages 61-88, 2009
10.1613/jair.2591
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A new search algorithm for solving distributed constraint optimization problems (DisCOPs) is presented. Agents assign variables sequentially and compute bounds on partial assignments asynchronously. The asynchronous bounds computation is based on the propagation of partial assignments. The asynchronous forward-bounding algorithm (AFB) is a distributed optimization search algorithm that keeps one consistent partial assignment at all times. The algorithm is described in detail and its correctness proven. Experimental evaluation shows that AFB outperforms synchronous branch and bound by many orders of magnitude, and produces a phase transition as the tightness of the problem increases. This is an analogous effect to the phase transition that has been observed when local consistency maintenance is applied to MaxCSPs. The AFB algorithm is further enhanced by the addition of a backjumping mechanism, resulting in the AFB-BJ algorithm. Distributed backjumping is based on accumulated information on bounds of all values and on processing concurrently a queue of candidate goals for the next move back. The AFB-BJ algorithm is compared experimentally to other DisCOP algorithms (ADOPT, DPOP, OptAPO) and is shown to be a very efficient algorithm for DisCOPs.
[ { "created": "Wed, 15 Jan 2014 04:54:38 GMT", "version": "v1" } ]
2014-01-16
[ [ "Gershman", "Amir", "" ], [ "Meisels", "Amnon", "" ], [ "Zivan", "Roie", "" ] ]
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1401.3443
Antonis Kakas
Antonis Kakas, Paolo Mancarella, Fariba Sadri, Kostas Stathis, Francesca Toni
Computational Logic Foundations of KGP Agents
null
Journal Of Artificial Intelligence Research, Volume 33, pages 285-348, 2008
10.1613/jair.2596
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents the computational logic foundations of a model of agency called the KGP (Knowledge, Goals and Plan model. This model allows the specification of heterogeneous agents that can interact with each other, and can exhibit both proactive and reactive behaviour allowing them to function in dynamic environments by adjusting their goals and plans when changes happen in such environments. KGP provides a highly modular agent architecture that integrates a collection of reasoning and physical capabilities, synthesised within transitions that update the agents state in response to reasoning, sensing and acting. Transitions are orchestrated by cycle theories that specify the order in which transitions are executed while taking into account the dynamic context and agent preferences, as well as selection operators for providing inputs to transitions.
[ { "created": "Wed, 15 Jan 2014 04:54:59 GMT", "version": "v1" } ]
2014-01-16
[ [ "Kakas", "Antonis", "" ], [ "Mancarella", "Paolo", "" ], [ "Sadri", "Fariba", "" ], [ "Stathis", "Kostas", "" ], [ "Toni", "Francesca", "" ] ]
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1401.3444
Didier Dubois
Didier Dubois, H\'el\`ene Fargier, Jean-Fran\c{c}ois Bonnefon
On the Qualitative Comparison of Decisions Having Positive and Negative Features
null
Journal Of Artificial Intelligence Research, Volume 32, pages 385-417, 2008
10.1613/jair.2520
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Making a decision is often a matter of listing and comparing positive and negative arguments. In such cases, the evaluation scale for decisions should be considered bipolar, that is, negative and positive values should be explicitly distinguished. That is what is done, for example, in Cumulative Prospect Theory. However, contraryto the latter framework that presupposes genuine numerical assessments, human agents often decide on the basis of an ordinal ranking of the pros and the cons, and by focusing on the most salient arguments. In other terms, the decision process is qualitative as well as bipolar. In this article, based on a bipolar extension of possibility theory, we define and axiomatically characterize several decision rules tailored for the joint handling of positive and negative arguments in an ordinal setting. The simplest rules can be viewed as extensions of the maximin and maximax criteria to the bipolar case, and consequently suffer from poor decisive power. More decisive rules that refine the former are also proposed. These refinements agree both with principles of efficiency and with the spirit of order-of-magnitude reasoning, that prevails in qualitative decision theory. The most refined decision rule uses leximin rankings of the pros and the cons, and the ideas of counting arguments of equal strength and cancelling pros by cons. It is shown to come down to a special case of Cumulative Prospect Theory, and to subsume the Take the Best heuristic studied by cognitive psychologists.
[ { "created": "Wed, 15 Jan 2014 04:55:20 GMT", "version": "v1" } ]
2014-01-16
[ [ "Dubois", "Didier", "" ], [ "Fargier", "Hélène", "" ], [ "Bonnefon", "Jean-François", "" ] ]
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null
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1401.3446
Shiplu Hawlader
Md. Shiplu Hawlader and Saifuddin Md. Tareeq
Amino Acid Interaction Network Prediction using Multi-objective Optimization
null
null
10.5121/csit.2014.4113
null
cs.CE cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Protein can be represented by amino acid interaction network. This network is a graph whose vertices are the proteins amino acids and whose edges are the interactions between them. This interaction network is the first step of proteins three-dimensional structure prediction. In this paper we present a multi-objective evolutionary algorithm for interaction prediction and ant colony probabilistic optimization algorithm is used to confirm the interaction.
[ { "created": "Wed, 15 Jan 2014 04:59:08 GMT", "version": "v1" } ]
2014-01-16
[ [ "Hawlader", "Md. Shiplu", "" ], [ "Tareeq", "Saifuddin Md.", "" ] ]
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1401.3447
Saher Esmeir
Saher Esmeir, Shaul Markovitch
Anytime Induction of Low-cost, Low-error Classifiers: a Sampling-based Approach
null
Journal Of Artificial Intelligence Research, Volume 33, pages 1-31, 2008
10.1613/jair.2602
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Machine learning techniques are gaining prevalence in the production of a wide range of classifiers for complex real-world applications with nonuniform testing and misclassification costs. The increasing complexity of these applications poses a real challenge to resource management during learning and classification. In this work we introduce ACT (anytime cost-sensitive tree learner), a novel framework for operating in such complex environments. ACT is an anytime algorithm that allows learning time to be increased in return for lower classification costs. It builds a tree top-down and exploits additional time resources to obtain better estimations for the utility of the different candidate splits. Using sampling techniques, ACT approximates the cost of the subtree under each candidate split and favors the one with a minimal cost. As a stochastic algorithm, ACT is expected to be able to escape local minima, into which greedy methods may be trapped. Experiments with a variety of datasets were conducted to compare ACT to the state-of-the-art cost-sensitive tree learners. The results show that for the majority of domains ACT produces significantly less costly trees. ACT also exhibits good anytime behavior with diminishing returns.
[ { "created": "Wed, 15 Jan 2014 05:09:07 GMT", "version": "v1" } ]
2014-01-16
[ [ "Esmeir", "Saher", "" ], [ "Markovitch", "Shaul", "" ] ]
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1401.3448
Robert Mateescu
Robert Mateescu, Rina Dechter, Radu Marinescu
AND/OR Multi-Valued Decision Diagrams (AOMDDs) for Graphical Models
null
Journal Of Artificial Intelligence Research, Volume 33, pages 465-519, 2008
10.1613/jair.2605
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Inspired by the recently introduced framework of AND/OR search spaces for graphical models, we propose to augment Multi-Valued Decision Diagrams (MDD) with AND nodes, in order to capture function decomposition structure and to extend these compiled data structures to general weighted graphical models (e.g., probabilistic models). We present the AND/OR Multi-Valued Decision Diagram (AOMDD) which compiles a graphical model into a canonical form that supports polynomial (e.g., solution counting, belief updating) or constant time (e.g. equivalence of graphical models) queries. We provide two algorithms for compiling the AOMDD of a graphical model. The first is search-based, and works by applying reduction rules to the trace of the memory intensive AND/OR search algorithm. The second is inference-based and uses a Bucket Elimination schedule to combine the AOMDDs of the input functions via the the APPLY operator. For both algorithms, the compilation time and the size of the AOMDD are, in the worst case, exponential in the treewidth of the graphical model, rather than pathwidth as is known for ordered binary decision diagrams (OBDDs). We introduce the concept of semantic treewidth, which helps explain why the size of a decision diagram is often much smaller than the worst case bound. We provide an experimental evaluation that demonstrates the potential of AOMDDs.
[ { "created": "Wed, 15 Jan 2014 05:09:35 GMT", "version": "v1" } ]
2014-01-16
[ [ "Mateescu", "Robert", "" ], [ "Dechter", "Rina", "" ], [ "Marinescu", "Radu", "" ] ]
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1401.3449
Vincent Conitzer
Vincent Conitzer
Eliciting Single-Peaked Preferences Using Comparison Queries
null
Journal Of Artificial Intelligence Research, Volume 35, pages 161-191, 2009
10.1613/jair.2606
null
cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Voting is a general method for aggregating the preferences of multiple agents. Each agent ranks all the possible alternatives, and based on this, an aggregate ranking of the alternatives (or at least a winning alternative) is produced. However, when there are many alternatives, it is impractical to simply ask agents to report their complete preferences. Rather, the agents preferences, or at least the relevant parts thereof, need to be elicited. This is done by asking the agents a (hopefully small) number of simple queries about their preferences, such as comparison queries, which ask an agent to compare two of the alternatives. Prior work on preference elicitation in voting has focused on the case of unrestricted preferences. It has been shown that in this setting, it is sometimes necessary to ask each agent (almost) as many queries as would be required to determine an arbitrary ranking of the alternatives. In contrast, in this paper, we focus on single-peaked preferences. We show that such preferences can be elicited using only a linear number of comparison queries, if either the order with respect to which preferences are single-peaked is known, or at least one other agents complete preferences are known. We show that using a sublinear number of queries does not suffice. We also consider the case of cardinally single-peaked preferences. For this case, we show that if the alternatives cardinal positions are known, then an agents preferences can be elicited using only a logarithmic number of queries; however, we also show that if the cardinal positions are not known, then a sublinear number of queries does not suffice. We present experimental results for all elicitation algorithms. We also consider the problem of only eliciting enough information to determine the aggregate ranking, and show that even for this more modest objective, a sublinear number of queries per agent does not suffice for known ordinal or unknown cardinal positions. Finally, we discuss whether and how these techniques can be applied when preferences are almost single-peaked.
[ { "created": "Wed, 15 Jan 2014 05:10:11 GMT", "version": "v1" } ]
2014-01-16
[ [ "Conitzer", "Vincent", "" ] ]
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1401.3450
Tal Grinshpoun
Tal Grinshpoun, Amnon Meisels
Completeness and Performance Of The APO Algorithm
arXiv admin note: substantial text overlap with arXiv:1109.6052 by other authors
Journal Of Artificial Intelligence Research, Volume 33, pages 223-258, 2008
10.1613/jair.2611
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Asynchronous Partial Overlay (APO) is a search algorithm that uses cooperative mediation to solve Distributed Constraint Satisfaction Problems (DisCSPs). The algorithm partitions the search into different subproblems of the DisCSP. The original proof of completeness of the APO algorithm is based on the growth of the size of the subproblems. The present paper demonstrates that this expected growth of subproblems does not occur in some situations, leading to a termination problem of the algorithm. The problematic parts in the APO algorithm that interfere with its completeness are identified and necessary modifications to the algorithm that fix these problematic parts are given. The resulting version of the algorithm, Complete Asynchronous Partial Overlay (CompAPO), ensures its completeness. Formal proofs for the soundness and completeness of CompAPO are given. A detailed performance evaluation of CompAPO comparing it to other DisCSP algorithms is presented, along with an extensive experimental evaluation of the algorithm's unique behavior. Additionally, an optimization version of the algorithm, CompOptAPO, is presented, discussed, and evaluated.
[ { "created": "Wed, 15 Jan 2014 05:10:44 GMT", "version": "v1" } ]
2014-01-16
[ [ "Grinshpoun", "Tal", "" ], [ "Meisels", "Amnon", "" ] ]
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1401.3451
Radu Jurca
Radu Jurca, Boi Faltings
Mechanisms for Making Crowds Truthful
null
Journal Of Artificial Intelligence Research, Volume 34, pages 209-253, 2009
10.1613/jair.2621
null
cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider schemes for obtaining truthful reports on a common but hidden signal from large groups of rational, self-interested agents. One example are online feedback mechanisms, where users provide observations about the quality of a product or service so that other users can have an accurate idea of what quality they can expect. However, (i) providing such feedback is costly, and (ii) there are many motivations for providing incorrect feedback. Both problems can be addressed by reward schemes which (i) cover the cost of obtaining and reporting feedback, and (ii) maximize the expected reward of a rational agent who reports truthfully. We address the design of such incentive-compatible rewards for feedback generated in environments with pure adverse selection. Here, the correlation between the true knowledge of an agent and her beliefs regarding the likelihoods of reports of other agents can be exploited to make honest reporting a Nash equilibrium. In this paper we extend existing methods for designing incentive-compatible rewards by also considering collusion. We analyze different scenarios, where, for example, some or all of the agents collude. For each scenario we investigate whether a collusion-resistant, incentive-compatible reward scheme exists, and use automated mechanism design to specify an algorithm for deriving an efficient reward mechanism.
[ { "created": "Wed, 15 Jan 2014 05:11:17 GMT", "version": "v1" } ]
2014-01-16
[ [ "Jurca", "Radu", "" ], [ "Faltings", "Boi", "" ] ]
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1401.3453
Judy Goldsmith
Judy Goldsmith, Jerome Lang, Miroslaw Truszczyski, Nic Wilson
The Computational Complexity of Dominance and Consistency in CP-Nets
null
Journal Of Artificial Intelligence Research, Volume 33, pages 403-432, 2008
10.1613/jair.2627
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We investigate the computational complexity of testing dominance and consistency in CP-nets. Previously, the complexity of dominance has been determined for restricted classes in which the dependency graph of the CP-net is acyclic. However, there are preferences of interest that define cyclic dependency graphs; these are modeled with general CP-nets. In our main results, we show here that both dominance and consistency for general CP-nets are PSPACE-complete. We then consider the concept of strong dominance, dominance equivalence and dominance incomparability, and several notions of optimality, and identify the complexity of the corresponding decision problems. The reductions used in the proofs are from STRIPS planning, and thus reinforce the earlier established connections between both areas.
[ { "created": "Wed, 15 Jan 2014 05:13:25 GMT", "version": "v1" } ]
2014-01-16
[ [ "Goldsmith", "Judy", "" ], [ "Lang", "Jerome", "" ], [ "Truszczyski", "Miroslaw", "" ], [ "Wilson", "Nic", "" ] ]
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1401.3454
Sherief Abdallah
Sherief Abdallah, Victor Lesser
A Multiagent Reinforcement Learning Algorithm with Non-linear Dynamics
null
Journal Of Artificial Intelligence Research, Volume 33, pages 521-549, 2008
10.1613/jair.2628
null
cs.LG cs.MA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Several multiagent reinforcement learning (MARL) algorithms have been proposed to optimize agents decisions. Due to the complexity of the problem, the majority of the previously developed MARL algorithms assumed agents either had some knowledge of the underlying game (such as Nash equilibria) and/or observed other agents actions and the rewards they received. We introduce a new MARL algorithm called the Weighted Policy Learner (WPL), which allows agents to reach a Nash Equilibrium (NE) in benchmark 2-player-2-action games with minimum knowledge. Using WPL, the only feedback an agent needs is its own local reward (the agent does not observe other agents actions or rewards). Furthermore, WPL does not assume that agents know the underlying game or the corresponding Nash Equilibrium a priori. We experimentally show that our algorithm converges in benchmark two-player-two-action games. We also show that our algorithm converges in the challenging Shapleys game where previous MARL algorithms failed to converge without knowing the underlying game or the NE. Furthermore, we show that WPL outperforms the state-of-the-art algorithms in a more realistic setting of 100 agents interacting and learning concurrently. An important aspect of understanding the behavior of a MARL algorithm is analyzing the dynamics of the algorithm: how the policies of multiple learning agents evolve over time as agents interact with one another. Such an analysis not only verifies whether agents using a given MARL algorithm will eventually converge, but also reveals the behavior of the MARL algorithm prior to convergence. We analyze our algorithm in two-player-two-action games and show that symbolically proving WPLs convergence is difficult, because of the non-linear nature of WPLs dynamics, unlike previous MARL algorithms that had either linear or piece-wise-linear dynamics. Instead, we numerically solve WPLs dynamics differential equations and compare the solution to the dynamics of previous MARL algorithms.
[ { "created": "Wed, 15 Jan 2014 05:13:47 GMT", "version": "v1" } ]
2014-01-16
[ [ "Abdallah", "Sherief", "" ], [ "Lesser", "Victor", "" ] ]
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1401.3455
Prashant Doshi
Prashant Doshi, Piotr J. Gmytrasiewicz
Monte Carlo Sampling Methods for Approximating Interactive POMDPs
null
Journal Of Artificial Intelligence Research, Volume 34, pages 297-337, 2009
10.1613/jair.2630
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Partially observable Markov decision processes (POMDPs) provide a principled framework for sequential planning in uncertain single agent settings. An extension of POMDPs to multiagent settings, called interactive POMDPs (I-POMDPs), replaces POMDP belief spaces with interactive hierarchical belief systems which represent an agent's belief about the physical world, about beliefs of other agents, and about their beliefs about others' beliefs. This modification makes the difficulties of obtaining solutions due to complexity of the belief and policy spaces even more acute. We describe a general method for obtaining approximate solutions of I-POMDPs based on particle filtering (PF). We introduce the interactive PF, which descends the levels of the interactive belief hierarchies and samples and propagates beliefs at each level. The interactive PF is able to mitigate the belief space complexity, but it does not address the policy space complexity. To mitigate the policy space complexity -- sometimes also called the curse of history -- we utilize a complementary method based on sampling likely observations while building the look ahead reachability tree. While this approach does not completely address the curse of history, it beats back the curse's impact substantially. We provide experimental results and chart future work.
[ { "created": "Wed, 15 Jan 2014 05:14:08 GMT", "version": "v1" } ]
2014-01-16
[ [ "Doshi", "Prashant", "" ], [ "Gmytrasiewicz", "Piotr J.", "" ] ]
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1401.3456
Radek Erban
Radek Erban
From Molecular Dynamics to Brownian Dynamics
Submitted to Proceedings of the Royal Society A
null
10.1098/rspa.2014.0036
null
physics.comp-ph physics.bio-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Three coarse-grained molecular dynamics (MD) models are investigated with the aim of developing and analyzing multiscale methods which use MD simulations in parts of the computational domain and (less detailed) Brownian dynamics (BD) simulations in the remainder of the domain. The first MD model is formulated in one spatial dimension. It is based on elastic collisions of heavy molecules (e.g. proteins) with light point particles (e.g. water molecules). Two three-dimensional MD models are then investigated. The obtained results are applied to a simplified model of protein binding to receptors on the cellular membrane. It is shown that modern BD simulators of intracellular processes can be used in the bulk and accurately coupled with a (more detailed) MD model of protein binding which is used close to the membrane.
[ { "created": "Wed, 15 Jan 2014 05:14:15 GMT", "version": "v1" } ]
2015-06-18
[ [ "Erban", "Radek", "" ] ]
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1401.3457
S.R.K. Branavan
S.R.K. Branavan, Harr Chen, Jacob Eisenstein, Regina Barzilay
Learning Document-Level Semantic Properties from Free-Text Annotations
null
Journal Of Artificial Intelligence Research, Volume 34, pages 569-603, 2009
10.1613/jair.2633
null
cs.CL cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents a new method for inferring the semantic properties of documents by leveraging free-text keyphrase annotations. Such annotations are becoming increasingly abundant due to the recent dramatic growth in semi-structured, user-generated online content. One especially relevant domain is product reviews, which are often annotated by their authors with pros/cons keyphrases such as a real bargain or good value. These annotations are representative of the underlying semantic properties; however, unlike expert annotations, they are noisy: lay authors may use different labels to denote the same property, and some labels may be missing. To learn using such noisy annotations, we find a hidden paraphrase structure which clusters the keyphrases. The paraphrase structure is linked with a latent topic model of the review texts, enabling the system to predict the properties of unannotated documents and to effectively aggregate the semantic properties of multiple reviews. Our approach is implemented as a hierarchical Bayesian model with joint inference. We find that joint inference increases the robustness of the keyphrase clustering and encourages the latent topics to correlate with semantically meaningful properties. Multiple evaluations demonstrate that our model substantially outperforms alternative approaches for summarizing single and multiple documents into a set of semantically salient keyphrases.
[ { "created": "Wed, 15 Jan 2014 05:14:31 GMT", "version": "v1" } ]
2014-01-16
[ [ "Branavan", "S. R. K.", "" ], [ "Chen", "Harr", "" ], [ "Eisenstein", "Jacob", "" ], [ "Barzilay", "Regina", "" ] ]
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1401.3458
Fahiem Bacchus
Fahiem Bacchus, Shannon Dalmao, Toniann Pitassi
Solving #SAT and Bayesian Inference with Backtracking Search
null
Journal Of Artificial Intelligence Research, Volume 34, pages 391-442, 2009
10.1613/jair.2648
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Inference in Bayes Nets (BAYES) is an important problem with numerous applications in probabilistic reasoning. Counting the number of satisfying assignments of a propositional formula (#SAT) is a closely related problem of fundamental theoretical importance. Both these problems, and others, are members of the class of sum-of-products (SUMPROD) problems. In this paper we show that standard backtracking search when augmented with a simple memoization scheme (caching) can solve any sum-of-products problem with time complexity that is at least as good any other state-of-the-art exact algorithm, and that it can also achieve the best known time-space tradeoff. Furthermore, backtracking's ability to utilize more flexible variable orderings allows us to prove that it can achieve an exponential speedup over other standard algorithms for SUMPROD on some instances. The ideas presented here have been utilized in a number of solvers that have been applied to various types of sum-of-product problems. These system's have exploited the fact that backtracking can naturally exploit more of the problem's structure to achieve improved performance on a range of probleminstances. Empirical evidence of this performance gain has appeared in published works describing these solvers, and we provide references to these works.
[ { "created": "Wed, 15 Jan 2014 05:17:49 GMT", "version": "v1" } ]
2014-01-16
[ [ "Bacchus", "Fahiem", "" ], [ "Dalmao", "Shannon", "" ], [ "Pitassi", "Toniann", "" ] ]
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1401.3459
Maxim Binshtok
Maxim Binshtok, Ronen I. Brafman, Carmel Domshlak, Solomon Eyal Shimony
Generic Preferences over Subsets of Structured Objects
null
Journal Of Artificial Intelligence Research, Volume 34, pages 133-164, 2009
10.1613/jair.2653
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Various tasks in decision making and decision support systems require selecting a preferred subset of a given set of items. Here we focus on problems where the individual items are described using a set of characterizing attributes, and a generic preference specification is required, that is, a specification that can work with an arbitrary set of items. For example, preferences over the content of an online newspaper should have this form: At each viewing, the newspaper contains a subset of the set of articles currently available. Our preference specification over this subset should be provided offline, but we should be able to use it to select a subset of any currently available set of articles, e.g., based on their tags. We present a general approach for lifting formalisms for specifying preferences over objects with multiple attributes into ones that specify preferences over subsets of such objects. We also show how we can compute an optimal subset given such a specification in a relatively efficient manner. We provide an empirical evaluation of the approach as well as some worst-case complexity results.
[ { "created": "Wed, 15 Jan 2014 05:18:50 GMT", "version": "v1" } ]
2014-01-16
[ [ "Binshtok", "Maxim", "" ], [ "Brafman", "Ronen I.", "" ], [ "Domshlak", "Carmel", "" ], [ "Shimony", "Solomon Eyal", "" ] ]
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1401.3460
Daniel S. Bernstein
Daniel S. Bernstein, Christopher Amato, Eric A. Hansen, Shlomo Zilberstein
Policy Iteration for Decentralized Control of Markov Decision Processes
null
Journal Of Artificial Intelligence Research, Volume 34, pages 89-132, 2009
10.1613/jair.2667
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Coordination of distributed agents is required for problems arising in many areas, including multi-robot systems, networking and e-commerce. As a formal framework for such problems, we use the decentralized partially observable Markov decision process (DEC-POMDP). Though much work has been done on optimal dynamic programming algorithms for the single-agent version of the problem, optimal algorithms for the multiagent case have been elusive. The main contribution of this paper is an optimal policy iteration algorithm for solving DEC-POMDPs. The algorithm uses stochastic finite-state controllers to represent policies. The solution can include a correlation device, which allows agents to correlate their actions without communicating. This approach alternates between expanding the controller and performing value-preserving transformations, which modify the controller without sacrificing value. We present two efficient value-preserving transformations: one can reduce the size of the controller and the other can improve its value while keeping the size fixed. Empirical results demonstrate the usefulness of value-preserving transformations in increasing value while keeping controller size to a minimum. To broaden the applicability of the approach, we also present a heuristic version of the policy iteration algorithm, which sacrifices convergence to optimality. This algorithm further reduces the size of the controllers at each step by assuming that probability distributions over the other agents actions are known. While this assumption may not hold in general, it helps produce higher quality solutions in our test problems.
[ { "created": "Wed, 15 Jan 2014 05:20:25 GMT", "version": "v1" } ]
2014-01-16
[ [ "Bernstein", "Daniel S.", "" ], [ "Amato", "Christopher", "" ], [ "Hansen", "Eric A.", "" ], [ "Zilberstein", "Shlomo", "" ] ]
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1401.3461
Marek Petrik
Marek Petrik, Shlomo Zilberstein
A Bilinear Programming Approach for Multiagent Planning
null
Journal Of Artificial Intelligence Research, Volume 35, pages 235-274, 2009
10.1613/jair.2673
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Multiagent planning and coordination problems are common and known to be computationally hard. We show that a wide range of two-agent problems can be formulated as bilinear programs. We present a successive approximation algorithm that significantly outperforms the coverage set algorithm, which is the state-of-the-art method for this class of multiagent problems. Because the algorithm is formulated for bilinear programs, it is more general and simpler to implement. The new algorithm can be terminated at any time and-unlike the coverage set algorithm-it facilitates the derivation of a useful online performance bound. It is also much more efficient, on average reducing the computation time of the optimal solution by about four orders of magnitude. Finally, we introduce an automatic dimensionality reduction method that improves the effectiveness of the algorithm, extending its applicability to new domains and providing a new way to analyze a subclass of bilinear programs.
[ { "created": "Wed, 15 Jan 2014 05:21:26 GMT", "version": "v1" } ]
2014-01-16
[ [ "Petrik", "Marek", "" ], [ "Zilberstein", "Shlomo", "" ] ]
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1401.3462
Amarjeet Singh
Amarjeet Singh, Andreas Krause, Carlos Guestrin, William J. Kaiser
Efficient Informative Sensing using Multiple Robots
null
Journal Of Artificial Intelligence Research, Volume 34, pages 707-755, 2009
10.1613/jair.2674
null
cs.RO cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The need for efficient monitoring of spatio-temporal dynamics in large environmental applications, such as the water quality monitoring in rivers and lakes, motivates the use of robotic sensors in order to achieve sufficient spatial coverage. Typically, these robots have bounded resources, such as limited battery or limited amounts of time to obtain measurements. Thus, careful coordination of their paths is required in order to maximize the amount of information collected, while respecting the resource constraints. In this paper, we present an efficient approach for near-optimally solving the NP-hard optimization problem of planning such informative paths. In particular, we first develop eSIP (efficient Single-robot Informative Path planning), an approximation algorithm for optimizing the path of a single robot. Hereby, we use a Gaussian Process to model the underlying phenomenon, and use the mutual information between the visited locations and remainder of the space to quantify the amount of information collected. We prove that the mutual information collected using paths obtained by using eSIP is close to the information obtained by an optimal solution. We then provide a general technique, sequential allocation, which can be used to extend any single robot planning algorithm, such as eSIP, for the multi-robot problem. This procedure approximately generalizes any guarantees for the single-robot problem to the multi-robot case. We extensively evaluate the effectiveness of our approach on several experiments performed in-field for two important environmental sensing applications, lake and river monitoring, and simulation experiments performed using several real world sensor network data sets.
[ { "created": "Wed, 15 Jan 2014 05:21:51 GMT", "version": "v1" } ]
2014-01-16
[ [ "Singh", "Amarjeet", "" ], [ "Krause", "Andreas", "" ], [ "Guestrin", "Carlos", "" ], [ "Kaiser", "William J.", "" ] ]
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1401.3463
Roberto Sebastiani
Roberto Sebastiani, Michele Vescovi
Automated Reasoning in Modal and Description Logics via SAT Encoding: the Case Study of K(m)/ALC-Satisfiability
null
Journal Of Artificial Intelligence Research, Volume 35, pages 343-389, 2009
10.1613/jair.2675
null
cs.LO cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In the last two decades, modal and description logics have been applied to numerous areas of computer science, including knowledge representation, formal verification, database theory, distributed computing and, more recently, semantic web and ontologies. For this reason, the problem of automated reasoning in modal and description logics has been thoroughly investigated. In particular, many approaches have been proposed for efficiently handling the satisfiability of the core normal modal logic K(m), and of its notational variant, the description logic ALC. Although simple in structure, K(m)/ALC is computationally very hard to reason on, its satisfiability being PSPACE-complete. In this paper we start exploring the idea of performing automated reasoning tasks in modal and description logics by encoding them into SAT, so that to be handled by state-of-the-art SAT tools; as with most previous approaches, we begin our investigation from the satisfiability in K(m). We propose an efficient encoding, and we test it on an extensive set of benchmarks, comparing the approach with the main state-of-the-art tools available. Although the encoding is necessarily worst-case exponential, from our experiments we notice that, in practice, this approach can handle most or all the problems which are at the reach of the other approaches, with performances which are comparable with, or even better than, those of the current state-of-the-art tools.
[ { "created": "Wed, 15 Jan 2014 05:22:19 GMT", "version": "v1" } ]
2014-01-16
[ [ "Sebastiani", "Roberto", "" ], [ "Vescovi", "Michele", "" ] ]
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1401.3464
R\'on\'an Daly
R\'on\'an Daly, Qiang Shen
Learning Bayesian Network Equivalence Classes with Ant Colony Optimization
null
Journal Of Artificial Intelligence Research, Volume 35, pages 391-447, 2009
10.1613/jair.2681
null
cs.NE cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Bayesian networks are a useful tool in the representation of uncertain knowledge. This paper proposes a new algorithm called ACO-E, to learn the structure of a Bayesian network. It does this by conducting a search through the space of equivalence classes of Bayesian networks using Ant Colony Optimization (ACO). To this end, two novel extensions of traditional ACO techniques are proposed and implemented. Firstly, multiple types of moves are allowed. Secondly, moves can be given in terms of indices that are not based on construction graph nodes. The results of testing show that ACO-E performs better than a greedy search and other state-of-the-art and metaheuristic algorithms whilst searching in the space of equivalence classes.
[ { "created": "Wed, 15 Jan 2014 05:22:48 GMT", "version": "v1" } ]
2014-01-16
[ [ "Daly", "Rónán", "" ], [ "Shen", "Qiang", "" ] ]
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1401.3465
Steven de Jong
Steven de Jong, Simon Uyttendaele, Karl Tuyls
Learning to Reach Agreement in a Continuous Ultimatum Game
null
Journal Of Artificial Intelligence Research, Volume 33, pages 551-574, 2008
10.1613/jair.2685
null
cs.GT cs.SI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
It is well-known that acting in an individually rational manner, according to the principles of classical game theory, may lead to sub-optimal solutions in a class of problems named social dilemmas. In contrast, humans generally do not have much difficulty with social dilemmas, as they are able to balance personal benefit and group benefit. As agents in multi-agent systems are regularly confronted with social dilemmas, for instance in tasks such as resource allocation, these agents may benefit from the inclusion of mechanisms thought to facilitate human fairness. Although many of such mechanisms have already been implemented in a multi-agent systems context, their application is usually limited to rather abstract social dilemmas with a discrete set of available strategies (usually two). Given that many real-world examples of social dilemmas are actually continuous in nature, we extend this previous work to more general dilemmas, in which agents operate in a continuous strategy space. The social dilemma under study here is the well-known Ultimatum Game, in which an optimal solution is achieved if agents agree on a common strategy. We investigate whether a scale-free interaction network facilitates agents to reach agreement, especially in the presence of fixed-strategy agents that represent a desired (e.g. human) outcome. Moreover, we study the influence of rewiring in the interaction network. The agents are equipped with continuous-action learning automata and play a large number of random pairwise games in order to establish a common strategy. From our experiments, we may conclude that results obtained in discrete-strategy games can be generalized to continuous-strategy games to a certain extent: a scale-free interaction network structure allows agents to achieve agreement on a common strategy, and rewiring in the interaction network greatly enhances the agents ability to reach agreement. However, it also becomes clear that some alternative mechanisms, such as reputation and volunteering, have many subtleties involved and do not have convincing beneficial effects in the continuous case.
[ { "created": "Wed, 15 Jan 2014 05:23:19 GMT", "version": "v1" } ]
2014-01-16
[ [ "de Jong", "Steven", "" ], [ "Uyttendaele", "Simon", "" ], [ "Tuyls", "Karl", "" ] ]
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1401.3466
Talal Rahwan
Talal Rahwan, Sarvapali Dyanand Ramchurn, Nicholas Robert Jennings, Andrea Giovannucci
An Anytime Algorithm for Optimal Coalition Structure Generation
null
Journal Of Artificial Intelligence Research, Volume 34, pages 521-567, 2009
10.1613/jair.2695
null
cs.MA cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Coalition formation is a fundamental type of interaction that involves the creation of coherent groupings of distinct, autonomous, agents in order to efficiently achieve their individual or collective goals. Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of determining which of the many possible coalitions to form in order to achieve some goal. This usually requires calculating a value for every possible coalition, known as the coalition value, which indicates how beneficial that coalition would be if it was formed. Once these values are calculated, the agents usually need to find a combination of coalitions, in which every agent belongs to exactly one coalition, and by which the overall outcome of the system is maximized. However, this coalition structure generation problem is extremely challenging due to the number of possible solutions that need to be examined, which grows exponentially with the number of agents involved. To date, therefore, many algorithms have been proposed to solve this problem using different techniques ranging from dynamic programming, to integer programming, to stochastic search all of which suffer from major limitations relating to execution time, solution quality, and memory requirements. With this in mind, we develop an anytime algorithm to solve the coalition structure generation problem. Specifically, the algorithm uses a novel representation of the search space, which partitions the space of possible solutions into sub-spaces such that it is possible to compute upper and lower bounds on the values of the best coalition structures in them. These bounds are then used to identify the sub-spaces that have no potential of containing the optimal solution so that they can be pruned. The algorithm, then, searches through the remaining sub-spaces very efficiently using a branch-and-bound technique to avoid examining all the solutions within the searched subspace(s). In this setting, we prove that our algorithm enumerates all coalition structures efficiently by avoiding redundant and invalid solutions automatically. Moreover, in order to effectively test our algorithm we develop a new type of input distribution which allows us to generate more reliable benchmarks compared to the input distributions previously used in the field. Given this new distribution, we show that for 27 agents our algorithm is able to find solutions that are optimal in 0.175% of the time required by the fastest available algorithm in the literature. The algorithm is anytime, and if interrupted before it would have normally terminated, it can still provide a solution that is guaranteed to be within a bound from the optimal one. Moreover, the guarantees we provide on the quality of the solution are significantly better than those provided by the previous state of the art algorithms designed for this purpose. For example, for the worst case distribution given 25 agents, our algorithm is able to find a 90% efficient solution in around 10% of time it takes to find the optimal solution.
[ { "created": "Wed, 15 Jan 2014 05:23:56 GMT", "version": "v1" } ]
2014-01-16
[ [ "Rahwan", "Talal", "" ], [ "Ramchurn", "Sarvapali Dyanand", "" ], [ "Jennings", "Nicholas Robert", "" ], [ "Giovannucci", "Andrea", "" ] ]
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1401.3467
Omer Gim\'enez
Omer Gim\'enez, Anders Jonsson
Planning over Chain Causal Graphs for Variables with Domains of Size 5 Is NP-Hard
null
Journal Of Artificial Intelligence Research, Volume 34, pages 675-706, 2009
10.1613/jair.2742
null
cs.AI cs.CC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recently, considerable focus has been given to the problem of determining the boundary between tractable and intractable planning problems. In this paper, we study the complexity of planning in the class C_n of planning problems, characterized by unary operators and directed path causal graphs. Although this is one of the simplest forms of causal graphs a planning problem can have, we show that planning is intractable for C_n (unless P = NP), even if the domains of state variables have bounded size. In particular, we show that plan existence for C_n^k is NP-hard for k>=5 by reduction from CNFSAT. Here, k denotes the upper bound on the size of the state variable domains. Our result reduces the complexity gap for the class C_n^k to cases k=3 and k=4 only, since C_n^2 is known to be tractable.
[ { "created": "Wed, 15 Jan 2014 05:25:29 GMT", "version": "v1" } ]
2014-01-16
[ [ "Giménez", "Omer", "" ], [ "Jonsson", "Anders", "" ] ]
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1401.3468
Hector Geffner
Hector Palacios, Hector Geffner
Compiling Uncertainty Away in Conformant Planning Problems with Bounded Width
null
Journal Of Artificial Intelligence Research, Volume 35, pages 623-675, 2009
10.1613/jair.2708
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Conformant planning is the problem of finding a sequence of actions for achieving a goal in the presence of uncertainty in the initial state or action effects. The problem has been approached as a path-finding problem in belief space where good belief representations and heuristics are critical for scaling up. In this work, a different formulation is introduced for conformant problems with deterministic actions where they are automatically converted into classical ones and solved by an off-the-shelf classical planner. The translation maps literals L and sets of assumptions t about the initial situation, into new literals KL/t that represent that L must be true if t is initially true. We lay out a general translation scheme that is sound and establish the conditions under which the translation is also complete. We show that the complexity of the complete translation is exponential in a parameter of the problem called the conformant width, which for most benchmarks is bounded. The planner based on this translation exhibits good performance in comparison with existing planners, and is the basis for T0, the best performing planner in the Conformant Track of the 2006 International Planning Competition.
[ { "created": "Wed, 15 Jan 2014 05:27:00 GMT", "version": "v1" } ]
2014-01-16
[ [ "Palacios", "Hector", "" ], [ "Geffner", "Hector", "" ] ]
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1401.3469
Vicente Ruiz de Angulo
Vicente Ruiz de Angulo, Carme Torras
Exploiting Single-Cycle Symmetries in Continuous Constraint Problems
null
Journal Of Artificial Intelligence Research, Volume 34, pages 499-520, 2009
10.1613/jair.2711
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Symmetries in discrete constraint satisfaction problems have been explored and exploited in the last years, but symmetries in continuous constraint problems have not received the same attention. Here we focus on permutations of the variables consisting of one single cycle. We propose a procedure that takes advantage of these symmetries by interacting with a continuous constraint solver without interfering with it. A key concept in this procedure are the classes of symmetric boxes formed by bisecting a n-dimensional cube at the same point in all dimensions at the same time. We analyze these classes and quantify them as a function of the cube dimensionality. Moreover, we propose a simple algorithm to generate the representatives of all these classes for any number of variables at very high rates. A problem example from the chemical and#64257;eld and the cyclic n-roots problem are used to show the performance of the approach in practice.
[ { "created": "Wed, 15 Jan 2014 05:27:27 GMT", "version": "v1" } ]
2014-01-16
[ [ "de Angulo", "Vicente Ruiz", "" ], [ "Torras", "Carme", "" ] ]
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1401.3470
J\"org Hoffmann
J\"org Hoffmann, Piergiorgio Bertoli, Malte Helmert, Marco Pistore
Message-Based Web Service Composition, Integrity Constraints, and Planning under Uncertainty: A New Connection
null
Journal Of Artificial Intelligence Research, Volume 35, pages 49-117, 2009
10.1613/jair.2716
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Thanks to recent advances, AI Planning has become the underlying technique for several applications. Figuring prominently among these is automated Web Service Composition (WSC) at the "capability" level, where services are described in terms of preconditions and effects over ontological concepts. A key issue in addressing WSC as planning is that ontologies are not only formal vocabularies; they also axiomatize the possible relationships between concepts. Such axioms correspond to what has been termed "integrity constraints" in the actions and change literature, and applying a web service is essentially a belief update operation. The reasoning required for belief update is known to be harder than reasoning in the ontology itself. The support for belief update is severely limited in current planning tools. Our first contribution consists in identifying an interesting special case of WSC which is both significant and more tractable. The special case, which we term "forward effects", is characterized by the fact that every ramification of a web service application involves at least one new constant generated as output by the web service. We show that, in this setting, the reasoning required for belief update simplifies to standard reasoning in the ontology itself. This relates to, and extends, current notions of "message-based" WSC, where the need for belief update is removed by a strong (often implicit or informal) assumption of "locality" of the individual messages. We clarify the computational properties of the forward effects case, and point out a strong relation to standard notions of planning under uncertainty, suggesting that effective tools for the latter can be successfully adapted to address the former. Furthermore, we identify a significant sub-case, named "strictly forward effects", where an actual compilation into planning under uncertainty exists. This enables us to exploit off-the-shelf planning tools to solve message-based WSC in a general form that involves powerful ontologies, and requires reasoning about partial matches between concepts. We provide empirical evidence that this approach may be quite effective, using Conformant-FF as the underlying planner.
[ { "created": "Wed, 15 Jan 2014 05:27:56 GMT", "version": "v1" } ]
2014-01-16
[ [ "Hoffmann", "Jörg", "" ], [ "Bertoli", "Piergiorgio", "" ], [ "Helmert", "Malte", "" ], [ "Pistore", "Marco", "" ] ]
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1401.3471
Marco Zaffalon
Marco Zaffalon, Enrique Miranda
Conservative Inference Rule for Uncertain Reasoning under Incompleteness
null
Journal Of Artificial Intelligence Research, Volume 34, pages 757-821, 2009
10.1613/jair.2736
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we formulate the problem of inference under incomplete information in very general terms. This includes modelling the process responsible for the incompleteness, which we call the incompleteness process. We allow the process behaviour to be partly unknown. Then we use Walleys theory of coherent lower previsions, a generalisation of the Bayesian theory to imprecision, to derive the rule to update beliefs under incompleteness that logically follows from our assumptions, and that we call conservative inference rule. This rule has some remarkable properties: it is an abstract rule to update beliefs that can be applied in any situation or domain; it gives us the opportunity to be neither too optimistic nor too pessimistic about the incompleteness process, which is a necessary condition to draw reliable while strong enough conclusions; and it is a coherent rule, in the sense that it cannot lead to inconsistencies. We give examples to show how the new rule can be applied in expert systems, in parametric statistical inference, and in pattern classification, and discuss more generally the view of incompleteness processes defended here as well as some of its consequences.
[ { "created": "Wed, 15 Jan 2014 05:28:54 GMT", "version": "v1" } ]
2014-01-16
[ [ "Zaffalon", "Marco", "" ], [ "Miranda", "Enrique", "" ] ]
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1401.3472
Kaile Su
Kaile Su, Abdul Sattar, Guanfeng Lv, Yan Zhang
Variable Forgetting in Reasoning about Knowledge
null
Journal Of Artificial Intelligence Research, Volume 35, pages 677-716, 2009
10.1613/jair.2750
null
cs.LO cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we investigate knowledge reasoning within a simple framework called knowledge structure. We use variable forgetting as a basic operation for one agent to reason about its own or other agents\ knowledge. In our framework, two notions namely agents\ observable variables and the weakest sufficient condition play important roles in knowledge reasoning. Given a background knowledge base and a set of observable variables for each agent, we show that the notion of an agent knowing a formula can be defined as a weakest sufficient condition of the formula under background knowledge base. Moreover, we show how to capture the notion of common knowledge by using a generalized notion of weakest sufficient condition. Also, we show that public announcement operator can be conveniently dealt with via our notion of knowledge structure. Further, we explore the computational complexity of the problem whether an epistemic formula is realized in a knowledge structure. In the general case, this problem is PSPACE-hard; however, for some interesting subcases, it can be reduced to co-NP. Finally, we discuss possible applications of our framework in some interesting domains such as the automated analysis of the well-known muddy children puzzle and the verification of the revised Needham-Schroeder protocol. We believe that there are many scenarios where the natural presentation of the available information about knowledge is under the form of a knowledge structure. What makes it valuable compared with the corresponding multi-agent S5 Kripke structure is that it can be much more succinct.
[ { "created": "Wed, 15 Jan 2014 05:29:17 GMT", "version": "v1" } ]
2014-01-16
[ [ "Su", "Kaile", "" ], [ "Sattar", "Abdul", "" ], [ "Lv", "Guanfeng", "" ], [ "Zhang", "Yan", "" ] ]
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1401.3473
Sarvapali Dyanand Ramchurn
Sarvapali Dyanand Ramchurn, Claudio Mezzetti, Andrea Giovannucci, Juan Antonio Rodriguez-Aguilar, Rajdeep Kumar Dash, Nicholas Robert Jennings
Trust-Based Mechanisms for Robust and Efficient Task Allocation in the Presence of Execution Uncertainty
null
Journal Of Artificial Intelligence Research, Volume 35, pages 119-159, 2009
10.1613/jair.2751
null
cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Vickrey-Clarke-Groves (VCG) mechanisms are often used to allocate tasks to selfish and rational agents. VCG mechanisms are incentive compatible, direct mechanisms that are efficient (i.e., maximise social utility) and individually rational (i.e., agents prefer to join rather than opt out). However, an important assumption of these mechanisms is that the agents will "always" successfully complete their allocated tasks. Clearly, this assumption is unrealistic in many real-world applications, where agents can, and often do, fail in their endeavours. Moreover, whether an agent is deemed to have failed may be perceived differently by different agents. Such subjective perceptions about an agents probability of succeeding at a given task are often captured and reasoned about using the notion of "trust". Given this background, in this paper we investigate the design of novel mechanisms that take into account the trust between agents when allocating tasks. Specifically, we develop a new class of mechanisms, called "trust-based mechanisms", that can take into account multiple subjective measures of the probability of an agent succeeding at a given task and produce allocations that maximise social utility, whilst ensuring that no agent obtains a negative utility. We then show that such mechanisms pose a challenging new combinatorial optimisation problem (that is NP-complete), devise a novel representation for solving the problem, and develop an effective integer programming solution (that can solve instances with about 2x10^5 possible allocations in 40 seconds).
[ { "created": "Wed, 15 Jan 2014 05:29:44 GMT", "version": "v1" } ]
2014-01-16
[ [ "Ramchurn", "Sarvapali Dyanand", "" ], [ "Mezzetti", "Claudio", "" ], [ "Giovannucci", "Andrea", "" ], [ "Rodriguez-Aguilar", "Juan Antonio", "" ], [ "Dash", "Rajdeep Kumar", "" ], [ "Jennings", "Nicholas Robert", "" ] ]
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1401.3474
Andreas Krause
Andreas Krause, Carlos Guestrin
Optimal Value of Information in Graphical Models
null
Journal Of Artificial Intelligence Research, Volume 35, pages 557-591, 2009
10.1613/jair.2737
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Many real-world decision making tasks require us to choose among several expensive observations. In a sensor network, for example, it is important to select the subset of sensors that is expected to provide the strongest reduction in uncertainty. In medical decision making tasks, one needs to select which tests to administer before deciding on the most effective treatment. It has been general practice to use heuristic-guided procedures for selecting observations. In this paper, we present the first efficient optimal algorithms for selecting observations for a class of probabilistic graphical models. For example, our algorithms allow to optimally label hidden variables in Hidden Markov Models (HMMs). We provide results for both selecting the optimal subset of observations, and for obtaining an optimal conditional observation plan. Furthermore we prove a surprising result: In most graphical models tasks, if one designs an efficient algorithm for chain graphs, such as HMMs, this procedure can be generalized to polytree graphical models. We prove that the optimizing value of information is $NP^{PP}$-hard even for polytrees. It also follows from our results that just computing decision theoretic value of information objective functions, which are commonly used in practice, is a #P-complete problem even on Naive Bayes models (a simple special case of polytrees). In addition, we consider several extensions, such as using our algorithms for scheduling observation selection for multiple sensors. We demonstrate the effectiveness of our approach on several real-world datasets, including a prototype sensor network deployment for energy conservation in buildings.
[ { "created": "Wed, 15 Jan 2014 05:30:52 GMT", "version": "v1" } ]
2014-01-16
[ [ "Krause", "Andreas", "" ], [ "Guestrin", "Carlos", "" ] ]
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1401.3475
Meghyn Bienvenu
Meghyn Bienvenu
Prime Implicates and Prime Implicants: From Propositional to Modal Logic
null
Journal Of Artificial Intelligence Research, Volume 36, pages 71-128, 2009
10.1613/jair.2754
null
cs.LO cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Prime implicates and prime implicants have proven relevant to a number of areas of artificial intelligence, most notably abductive reasoning and knowledge compilation. The purpose of this paper is to examine how these notions might be appropriately extended from propositional logic to the modal logic K. We begin the paper by considering a number of potential definitions of clauses and terms for K. The different definitions are evaluated with respect to a set of syntactic, semantic, and complexity-theoretic properties characteristic of the propositional definition. We then compare the definitions with respect to the properties of the notions of prime implicates and prime implicants that they induce. While there is no definition that perfectly generalizes the propositional notions, we show that there does exist one definition which satisfies many of the desirable properties of the propositional case. In the second half of the paper, we consider the computational properties of the selected definition. To this end, we provide sound and complete algorithms for generating and recognizing prime implicates, and we show the prime implicate recognition task to be PSPACE-complete. We also prove upper and lower bounds on the size and number of prime implicates. While the paper focuses on the logic K, all of our results hold equally well for multi-modal K and for concept expressions in the description logic ALC.
[ { "created": "Wed, 15 Jan 2014 05:31:28 GMT", "version": "v1" } ]
2014-01-16
[ [ "Bienvenu", "Meghyn", "" ] ]
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1401.3476
Piero A. Bonatti
Piero A. Bonatti, Carsten Lutz, Frank Wolter
The Complexity of Circumscription in DLs
null
Journal Of Artificial Intelligence Research, Volume 35, pages 717-773, 2009
10.1613/jair.2763
null
cs.LO cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
As fragments of first-order logic, Description logics (DLs) do not provide nonmonotonic features such as defeasible inheritance and default rules. Since many applications would benefit from the availability of such features, several families of nonmonotonic DLs have been developed that are mostly based on default logic and autoepistemic logic. In this paper, we consider circumscription as an interesting alternative approach to nonmonotonic DLs that, in particular, supports defeasible inheritance in a natural way. We study DLs extended with circumscription under different language restrictions and under different constraints on the sets of minimized, fixed, and varying predicates, and pinpoint the exact computational complexity of reasoning for DLs ranging from ALC to ALCIO and ALCQO. When the minimized and fixed predicates include only concept names but no role names, then reasoning is complete for NExpTime^NP. It becomes complete for NP^NExpTime when the number of minimized and fixed predicates is bounded by a constant. If roles can be minimized or fixed, then complexity ranges from NExpTime^NP to undecidability.
[ { "created": "Wed, 15 Jan 2014 05:32:08 GMT", "version": "v1" } ]
2014-01-16
[ [ "Bonatti", "Piero A.", "" ], [ "Lutz", "Carsten", "" ], [ "Wolter", "Frank", "" ] ]
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1401.3477
Jos\'e Enrique Gallardo
Jos\'e Enrique Gallardo, Carlos Cotta, Antonio Jos\'e Fern\'andez
Solving Weighted Constraint Satisfaction Problems with Memetic/Exact Hybrid Algorithms
arXiv admin note: substantial text overlap with arXiv:0812.4170
Journal Of Artificial Intelligence Research, Volume 35, pages 533-555, 2009
10.1613/jair.2770
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A weighted constraint satisfaction problem (WCSP) is a constraint satisfaction problem in which preferences among solutions can be expressed. Bucket elimination is a complete technique commonly used to solve this kind of constraint satisfaction problem. When the memory required to apply bucket elimination is too high, a heuristic method based on it (denominated mini-buckets) can be used to calculate bounds for the optimal solution. Nevertheless, the curse of dimensionality makes these techniques impractical on large scale problems. In response to this situation, we present a memetic algorithm for WCSPs in which bucket elimination is used as a mechanism for recombining solutions, providing the best possible child from the parental set. Subsequently, a multi-level model in which this exact/metaheuristic hybrid is further hybridized with branch-and-bound techniques and mini-buckets is studied. As a case study, we have applied these algorithms to the resolution of the maximum density still life problem, a hard constraint optimization problem based on Conways game of life. The resulting algorithm consistently finds optimal patterns for up to date solved instances in less time than current approaches. Moreover, it is shown that this proposal provides new best known solutions for very large instances.
[ { "created": "Wed, 15 Jan 2014 05:32:38 GMT", "version": "v1" } ]
2014-01-16
[ [ "Gallardo", "José Enrique", "" ], [ "Cotta", "Carlos", "" ], [ "Fernández", "Antonio José", "" ] ]
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1401.3478
Facundo Bromberg
Facundo Bromberg, Dimitris Margaritis, Vasant Honavar
Efficient Markov Network Structure Discovery Using Independence Tests
null
Journal Of Artificial Intelligence Research, Volume 35, pages 449-484, 2009
10.1613/jair.2773
null
cs.LG cs.AI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present two algorithms for learning the structure of a Markov network from data: GSMN* and GSIMN. Both algorithms use statistical independence tests to infer the structure by successively constraining the set of structures consistent with the results of these tests. Until very recently, algorithms for structure learning were based on maximum likelihood estimation, which has been proved to be NP-hard for Markov networks due to the difficulty of estimating the parameters of the network, needed for the computation of the data likelihood. The independence-based approach does not require the computation of the likelihood, and thus both GSMN* and GSIMN can compute the structure efficiently (as shown in our experiments). GSMN* is an adaptation of the Grow-Shrink algorithm of Margaritis and Thrun for learning the structure of Bayesian networks. GSIMN extends GSMN* by additionally exploiting Pearls well-known properties of the conditional independence relation to infer novel independences from known ones, thus avoiding the performance of statistical tests to estimate them. To accomplish this efficiently GSIMN uses the Triangle theorem, also introduced in this work, which is a simplified version of the set of Markov axioms. Experimental comparisons on artificial and real-world data sets show GSIMN can yield significant savings with respect to GSMN*, while generating a Markov network with comparable or in some cases improved quality. We also compare GSIMN to a forward-chaining implementation, called GSIMN-FCH, that produces all possible conditional independences resulting from repeatedly applying Pearls theorems on the known conditional independence tests. The results of this comparison show that GSIMN, by the sole use of the Triangle theorem, is nearly optimal in terms of the set of independences tests that it infers.
[ { "created": "Wed, 15 Jan 2014 05:33:29 GMT", "version": "v1" } ]
2014-01-16
[ [ "Bromberg", "Facundo", "" ], [ "Margaritis", "Dimitris", "" ], [ "Honavar", "Vasant", "" ] ]
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1401.3479
Yllias Chali
Yllias Chali, Shafiq Rayhan Joty, Sadid A. Hasan
Complex Question Answering: Unsupervised Learning Approaches and Experiments
null
Journal Of Artificial Intelligence Research, Volume 35, pages 1-47, 2009
10.1613/jair.2784
null
cs.CL cs.IR cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Complex questions that require inferencing and synthesizing information from multiple documents can be seen as a kind of topic-oriented, informative multi-document summarization where the goal is to produce a single text as a compressed version of a set of documents with a minimum loss of relevant information. In this paper, we experiment with one empirical method and two unsupervised statistical machine learning techniques: K-means and Expectation Maximization (EM), for computing relative importance of the sentences. We compare the results of these approaches. Our experiments show that the empirical approach outperforms the other two techniques and EM performs better than K-means. However, the performance of these approaches depends entirely on the feature set used and the weighting of these features. In order to measure the importance and relevance to the user query we extract different kinds of features (i.e. lexical, lexical semantic, cosine similarity, basic element, tree kernel based syntactic and shallow-semantic) for each of the document sentences. We use a local search technique to learn the weights of the features. To the best of our knowledge, no study has used tree kernel functions to encode syntactic/semantic information for more complex tasks such as computing the relatedness between the query sentences and the document sentences in order to generate query-focused summaries (or answers to complex questions). For each of our methods of generating summaries (i.e. empirical, K-means and EM) we show the effects of syntactic and shallow-semantic features over the bag-of-words (BOW) features.
[ { "created": "Wed, 15 Jan 2014 05:33:57 GMT", "version": "v1" } ]
2014-01-16
[ [ "Chali", "Yllias", "" ], [ "Joty", "Shafiq Rayhan", "" ], [ "Hasan", "Sadid A.", "" ] ]
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1401.3481
Matthias Zytnicki
Matthias Zytnicki, Christine Gaspin, Simon de Givry, Thomas Schiex
Bounds Arc Consistency for Weighted CSPs
null
Journal Of Artificial Intelligence Research, Volume 35, pages 593-621, 2009
10.1613/jair.2797
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Weighted Constraint Satisfaction Problem (WCSP) framework allows representing and solving problems involving both hard constraints and cost functions. It has been applied to various problems, including resource allocation, bioinformatics, scheduling, etc. To solve such problems, solvers usually rely on branch-and-bound algorithms equipped with local consistency filtering, mostly soft arc consistency. However, these techniques are not well suited to solve problems with very large domains. Motivated by the resolution of an RNA gene localization problem inside large genomic sequences, and in the spirit of bounds consistency for large domains in crisp CSPs, we introduce soft bounds arc consistency, a new weighted local consistency specifically designed for WCSP with very large domains. Compared to soft arc consistency, BAC provides significantly improved time and space asymptotic complexity. In this paper, we show how the semantics of cost functions can be exploited to further improve the time complexity of BAC. We also compare both in theory and in practice the efficiency of BAC on a WCSP with bounds consistency enforced on a crisp CSP using cost variables. On two different real problems modeled as WCSP, including our RNA gene localization problem, we observe that maintaining bounds arc consistency outperforms arc consistency and also improves over bounds consistency enforced on a constraint model with cost variables.
[ { "created": "Wed, 15 Jan 2014 05:34:30 GMT", "version": "v1" } ]
2014-01-16
[ [ "Zytnicki", "Matthias", "" ], [ "Gaspin", "Christine", "" ], [ "de Givry", "Simon", "" ], [ "Schiex", "Thomas", "" ] ]
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1401.3482
Estela Saquete
Estela Saquete, Jose Luis Vicedo, Patricio Mart\'inez-Barco, Rafael Mu\~noz, Hector Llorens
Enhancing QA Systems with Complex Temporal Question Processing Capabilities
null
Journal Of Artificial Intelligence Research, Volume 35, pages 775-811, 2009
10.1613/jair.2805
null
cs.CL cs.AI cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents a multilayered architecture that enhances the capabilities of current QA systems and allows different types of complex questions or queries to be processed. The answers to these questions need to be gathered from factual information scattered throughout different documents. Specifically, we designed a specialized layer to process the different types of temporal questions. Complex temporal questions are first decomposed into simple questions, according to the temporal relations expressed in the original question. In the same way, the answers to the resulting simple questions are recomposed, fulfilling the temporal restrictions of the original complex question. A novel aspect of this approach resides in the decomposition which uses a minimal quantity of resources, with the final aim of obtaining a portable platform that is easily extensible to other languages. In this paper we also present a methodology for evaluation of the decomposition of the questions as well as the ability of the implemented temporal layer to perform at a multilingual level. The temporal layer was first performed for English, then evaluated and compared with: a) a general purpose QA system (F-measure 65.47% for QA plus English temporal layer vs. 38.01% for the general QA system), and b) a well-known QA system. Much better results were obtained for temporal questions with the multilayered system. This system was therefore extended to Spanish and very good results were again obtained in the evaluation (F-measure 40.36% for QA plus Spanish temporal layer vs. 22.94% for the general QA system).
[ { "created": "Wed, 15 Jan 2014 05:35:49 GMT", "version": "v1" } ]
2014-01-16
[ [ "Saquete", "Estela", "" ], [ "Vicedo", "Jose Luis", "" ], [ "Martínez-Barco", "Patricio", "" ], [ "Muñoz", "Rafael", "" ], [ "Llorens", "Hector", "" ] ]
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1401.3483
Hai Leong Chieu
Hai Leong Chieu, Wee Sun Sun Lee
Relaxed Survey Propagation for The Weighted Maximum Satisfiability Problem
null
Journal Of Artificial Intelligence Research, Volume 36, pages 229-266, 2009
10.1613/jair.2808
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The survey propagation (SP) algorithm has been shown to work well on large instances of the random 3-SAT problem near its phase transition. It was shown that SP estimates marginals over covers that represent clusters of solutions. The SP-y algorithm generalizes SP to work on the maximum satisfiability (Max-SAT) problem, but the cover interpretation of SP does not generalize to SP-y. In this paper, we formulate the relaxed survey propagation (RSP) algorithm, which extends the SP algorithm to apply to the weighted Max-SAT problem. We show that RSP has an interpretation of estimating marginals over covers violating a set of clauses with minimal weight. This naturally generalizes the cover interpretation of SP. Empirically, we show that RSP outperforms SP-y and other state-of-the-art Max-SAT solvers on random Max-SAT instances. RSP also outperforms state-of-the-art weighted Max-SAT solvers on random weighted Max-SAT instances.
[ { "created": "Wed, 15 Jan 2014 05:36:10 GMT", "version": "v1" } ]
2014-01-16
[ [ "Chieu", "Hai Leong", "" ], [ "Lee", "Wee Sun Sun", "" ] ]
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1401.3484
Tomi Janhunen
Tomi Janhunen, Emilia Oikarinen, Hans Tompits, Stefan Woltran
Modularity Aspects of Disjunctive Stable Models
null
Journal Of Artificial Intelligence Research, Volume 35, pages 813-857, 2009
10.1613/jair.2810
null
cs.LO cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Practically all programming languages allow the programmer to split a program into several modules which brings along several advantages in software development. In this paper, we are interested in the area of answer-set programming where fully declarative and nonmonotonic languages are applied. In this context, obtaining a modular structure for programs is by no means straightforward since the output of an entire program cannot in general be composed from the output of its components. To better understand the effects of disjunctive information on modularity we restrict the scope of analysis to the case of disjunctive logic programs (DLPs) subject to stable-model semantics. We define the notion of a DLP-function, where a well-defined input/output interface is provided, and establish a novel module theorem which indicates the compositionality of stable-model semantics for DLP-functions. The module theorem extends the well-known splitting-set theorem and enables the decomposition of DLP-functions given their strongly connected components based on positive dependencies induced by rules. In this setting, it is also possible to split shared disjunctive rules among components using a generalized shifting technique. The concept of modular equivalence is introduced for the mutual comparison of DLP-functions using a generalization of a translation-based verification method.
[ { "created": "Wed, 15 Jan 2014 05:36:41 GMT", "version": "v1" } ]
2014-01-16
[ [ "Janhunen", "Tomi", "" ], [ "Oikarinen", "Emilia", "" ], [ "Tompits", "Hans", "" ], [ "Woltran", "Stefan", "" ] ]
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1401.3485
Boris Motik
Boris Motik, Rob Shearer, Ian Horrocks
Hypertableau Reasoning for Description Logics
null
Journal Of Artificial Intelligence Research, Volume 36, pages 165-228, 2009
10.1613/jair.2811
null
cs.LO cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a novel reasoning calculus for the description logic SHOIQ^+---a knowledge representation formalism with applications in areas such as the Semantic Web. Unnecessary nondeterminism and the construction of large models are two primary sources of inefficiency in the tableau-based reasoning calculi used in state-of-the-art reasoners. In order to reduce nondeterminism, we base our calculus on hypertableau and hyperresolution calculi, which we extend with a blocking condition to ensure termination. In order to reduce the size of the constructed models, we introduce anywhere pairwise blocking. We also present an improved nominal introduction rule that ensures termination in the presence of nominals, inverse roles, and number restrictions---a combination of DL constructs that has proven notoriously difficult to handle. Our implementation shows significant performance improvements over state-of-the-art reasoners on several well-known ontologies.
[ { "created": "Wed, 15 Jan 2014 05:37:06 GMT", "version": "v1" } ]
2014-01-16
[ [ "Motik", "Boris", "" ], [ "Shearer", "Rob", "" ], [ "Horrocks", "Ian", "" ] ]
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1401.3486
Anders Jonsson
Anders Jonsson
The Role of Macros in Tractable Planning
null
Journal Of Artificial Intelligence Research, Volume 36, pages 471-511, 2009
10.1613/jair.2891
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents several new tractability results for planning based on macros. We describe an algorithm that optimally solves planning problems in a class that we call inverted tree reducible, and is provably tractable for several subclasses of this class. By using macros to store partial plans that recur frequently in the solution, the algorithm is polynomial in time and space even for exponentially long plans. We generalize the inverted tree reducible class in several ways and describe modifications of the algorithm to deal with these new classes. Theoretical results are validated in experiments.
[ { "created": "Wed, 15 Jan 2014 05:37:49 GMT", "version": "v1" } ]
2014-01-16
[ [ "Jonsson", "Anders", "" ] ]
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1401.3487
Alessandro Artale
Alessandro Artale, Diego Calvanese, Roman Kontchakov, Michael Zakharyaschev
The DL-Lite Family and Relations
null
Journal Of Artificial Intelligence Research, Volume 36, pages 1-69, 2009
10.1613/jair.2820
null
cs.LO cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The recently introduced series of description logics under the common moniker DL-Lite has attracted attention of the description logic and semantic web communities due to the low computational complexity of inference, on the one hand, and the ability to represent conceptual modeling formalisms, on the other. The main aim of this article is to carry out a thorough and systematic investigation of inference in extensions of the original DL-Lite logics along five axes: by (i) adding the Boolean connectives and (ii) number restrictions to concept constructs, (iii) allowing role hierarchies, (iv) allowing role disjointness, symmetry, asymmetry, reflexivity, irreflexivity and transitivity constraints, and (v) adopting or dropping the unique same assumption. We analyze the combined complexity of satisfiability for the resulting logics, as well as the data complexity of instance checking and answering positive existential queries. Our approach is based on embedding DL-Lite logics in suitable fragments of the one-variable first-order logic, which provides useful insights into their properties and, in particular, computational behavior.
[ { "created": "Wed, 15 Jan 2014 05:37:57 GMT", "version": "v1" } ]
2014-01-16
[ [ "Artale", "Alessandro", "" ], [ "Calvanese", "Diego", "" ], [ "Kontchakov", "Roman", "" ], [ "Zakharyaschev", "Michael", "" ] ]
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1401.3488
Harr Chen
Harr Chen, S.R.K. Branavan, Regina Barzilay, David R. Karger
Content Modeling Using Latent Permutations
null
Journal Of Artificial Intelligence Research, Volume 36, pages 129-163, 2009
10.1613/jair.2830
null
cs.IR cs.CL cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a novel Bayesian topic model for learning discourse-level document structure. Our model leverages insights from discourse theory to constrain latent topic assignments in a way that reflects the underlying organization of document topics. We propose a global model in which both topic selection and ordering are biased to be similar across a collection of related documents. We show that this space of orderings can be effectively represented using a distribution over permutations called the Generalized Mallows Model. We apply our method to three complementary discourse-level tasks: cross-document alignment, document segmentation, and information ordering. Our experiments show that incorporating our permutation-based model in these applications yields substantial improvements in performance over previously proposed methods.
[ { "created": "Wed, 15 Jan 2014 05:38:17 GMT", "version": "v1" } ]
2014-01-16
[ [ "Chen", "Harr", "" ], [ "Branavan", "S. R. K.", "" ], [ "Barzilay", "Regina", "" ], [ "Karger", "David R.", "" ] ]
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1401.3489
Robert Mateescu
Robert Mateescu, Kalev Kask, Vibhav Gogate, Rina Dechter
Join-Graph Propagation Algorithms
null
Journal Of Artificial Intelligence Research, Volume 37, pages 279-328, 2010
10.1613/jair.2842
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The paper investigates parameterized approximate message-passing schemes that are based on bounded inference and are inspired by Pearl's belief propagation algorithm (BP). We start with the bounded inference mini-clustering algorithm and then move to the iterative scheme called Iterative Join-Graph Propagation (IJGP), that combines both iteration and bounded inference. Algorithm IJGP belongs to the class of Generalized Belief Propagation algorithms, a framework that allowed connections with approximate algorithms from statistical physics and is shown empirically to surpass the performance of mini-clustering and belief propagation, as well as a number of other state-of-the-art algorithms on several classes of networks. We also provide insight into the accuracy of iterative BP and IJGP by relating these algorithms to well known classes of constraint propagation schemes.
[ { "created": "Wed, 15 Jan 2014 05:38:39 GMT", "version": "v1" } ]
2014-01-16
[ [ "Mateescu", "Robert", "" ], [ "Kask", "Kalev", "" ], [ "Gogate", "Vibhav", "" ], [ "Dechter", "Rina", "" ] ]
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1401.3490
William Yeoh
William Yeoh, Ariel Felner, Sven Koenig
BnB-ADOPT: An Asynchronous Branch-and-Bound DCOP Algorithm
null
Journal Of Artificial Intelligence Research, Volume 38, pages 85-133, 2010
10.1613/jair.2849
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Distributed constraint optimization (DCOP) problems are a popular way of formulating and solving agent-coordination problems. A DCOP problem is a problem where several agents coordinate their values such that the sum of the resulting constraint costs is minimal. It is often desirable to solve DCOP problems with memory-bounded and asynchronous algorithms. We introduce Branch-and-Bound ADOPT (BnB-ADOPT), a memory-bounded asynchronous DCOP search algorithm that uses the message-passing and communication framework of ADOPT (Modi, Shen, Tambe, and Yokoo, 2005), a well known memory-bounded asynchronous DCOP search algorithm, but changes the search strategy of ADOPT from best-first search to depth-first branch-and-bound search. Our experimental results show that BnB-ADOPT finds cost-minimal solutions up to one order of magnitude faster than ADOPT for a variety of large DCOP problems and is as fast as NCBB, a memory-bounded synchronous DCOP search algorithm, for most of these DCOP problems. Additionally, it is often desirable to find bounded-error solutions for DCOP problems within a reasonable amount of time since finding cost-minimal solutions is NP-hard. The existing bounded-error approximation mechanism allows users only to specify an absolute error bound on the solution cost but a relative error bound is often more intuitive. Thus, we present two new bounded-error approximation mechanisms that allow for relative error bounds and implement them on top of BnB-ADOPT.
[ { "created": "Wed, 15 Jan 2014 05:39:26 GMT", "version": "v1" } ]
2014-01-16
[ [ "Yeoh", "William", "" ], [ "Felner", "Ariel", "" ], [ "Koenig", "Sven", "" ] ]
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1401.3491
Emil Keyder
Emil Keyder, Hector Geffner
Soft Goals Can Be Compiled Away
null
Journal Of Artificial Intelligence Research, Volume 36, pages 547-556, 2009
10.1613/jair.2857
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Soft goals extend the classical model of planning with a simple model of preferences. The best plans are then not the ones with least cost but the ones with maximum utility, where the utility of a plan is the sum of the utilities of the soft goals achieved minus the plan cost. Finding plans with high utility appears to involve two linked problems: choosing a subset of soft goals to achieve and finding a low-cost plan to achieve them. New search algorithms and heuristics have been developed for planning with soft goals, and a new track has been introduced in the International Planning Competition (IPC) to test their performance. In this note, we show however that these extensions are not needed: soft goals do not increase the expressive power of the basic model of planning with action costs, as they can easily be compiled away. We apply this compilation to the problems of the net-benefit track of the most recent IPC, and show that optimal and satisficing cost-based planners do better on the compiled problems than optimal and satisficing net-benefit planners on the original problems with explicit soft goals. Furthermore, we show that penalties, or negative preferences expressing conditions to avoid, can also be compiled away using a similar idea.
[ { "created": "Wed, 15 Jan 2014 05:39:49 GMT", "version": "v1" } ]
2014-01-16
[ [ "Keyder", "Emil", "" ], [ "Geffner", "Hector", "" ] ]
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1401.3492
Frank Hutter
Frank Hutter, Thomas Stuetzle, Kevin Leyton-Brown, Holger H. Hoos
ParamILS: An Automatic Algorithm Configuration Framework
null
Journal Of Artificial Intelligence Research, Volume 36, pages 267-306, 2009
10.1613/jair.2861
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The identification of performance-optimizing parameter settings is an important part of the development and application of algorithms. We describe an automatic framework for this algorithm configuration problem. More formally, we provide methods for optimizing a target algorithm's performance on a given class of problem instances by varying a set of ordinal and/or categorical parameters. We review a family of local-search-based algorithm configuration procedures and present novel techniques for accelerating them by adaptively limiting the time spent for evaluating individual configurations. We describe the results of a comprehensive experimental evaluation of our methods, based on the configuration of prominent complete and incomplete algorithms for SAT. We also present what is, to our knowledge, the first published work on automatically configuring the CPLEX mixed integer programming solver. All the algorithms we considered had default parameter settings that were manually identified with considerable effort. Nevertheless, using our automated algorithm configuration procedures, we achieved substantial and consistent performance improvements.
[ { "created": "Wed, 15 Jan 2014 05:40:11 GMT", "version": "v1" } ]
2014-01-16
[ [ "Hutter", "Frank", "" ], [ "Stuetzle", "Thomas", "" ], [ "Leyton-Brown", "Kevin", "" ], [ "Hoos", "Holger H.", "" ] ]
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1401.3493
Uzi Zahavi
Uzi Zahavi, Ariel Felner, Neil Burch, Robert C. Holte
Predicting the Performance of IDA* using Conditional Distributions
null
Journal Of Artificial Intelligence Research, Volume 37, pages 41-83, 2010
10.1613/jair.2890
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Korf, Reid, and Edelkamp introduced a formula to predict the number of nodes IDA* will expand on a single iteration for a given consistent heuristic, and experimentally demonstrated that it could make very accurate predictions. In this paper we show that, in addition to requiring the heuristic to be consistent, their formulas predictions are accurate only at levels of the brute-force search tree where the heuristic values obey the unconditional distribution that they defined and then used in their formula. We then propose a new formula that works well without these requirements, i.e., it can make accurate predictions of IDA*s performance for inconsistent heuristics and if the heuristic values in any level do not obey the unconditional distribution. In order to achieve this we introduce the conditional distribution of heuristic values which is a generalization of their unconditional heuristic distribution. We also provide extensions of our formula that handle individual start states and the augmentation of IDA* with bidirectional pathmax (BPMX), a technique for propagating heuristic values when inconsistent heuristics are used. Experimental results demonstrate the accuracy of our new method and all its variations.
[ { "created": "Wed, 15 Jan 2014 05:41:44 GMT", "version": "v1" } ]
2014-01-16
[ [ "Zahavi", "Uzi", "" ], [ "Felner", "Ariel", "" ], [ "Burch", "Neil", "" ], [ "Holte", "Robert C.", "" ] ]
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1401.3494
Michal Feldman
Michal Feldman, Tami Tamir
Approximate Strong Equilibrium in Job Scheduling Games
null
Journal Of Artificial Intelligence Research, Volume 36, pages 387-414, 2009
10.1613/jair.2892
null
cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A Nash Equilibrium (NE) is a strategy profile resilient to unilateral deviations, and is predominantly used in the analysis of multiagent systems. A downside of NE is that it is not necessarily stable against deviations by coalitions. Yet, as we show in this paper, in some cases, NE does exhibit stability against coalitional deviations, in that the benefits from a joint deviation are bounded. In this sense, NE approximates strong equilibrium. Coalition formation is a key issue in multiagent systems. We provide a framework for quantifying the stability and the performance of various assignment policies and solution concepts in the face of coalitional deviations. Within this framework we evaluate a given configuration according to three measures: (i) IR_min: the maximal number alpha, such that there exists a coalition in which the minimal improvement ratio among the coalition members is alpha, (ii) IR_max: the maximal number alpha, such that there exists a coalition in which the maximal improvement ratio among the coalition members is alpha, and (iii) DR_max: the maximal possible damage ratio of an agent outside the coalition. We analyze these measures in job scheduling games on identical machines. In particular, we provide upper and lower bounds for the above three measures for both NE and the well-known assignment rule Longest Processing Time (LPT). Our results indicate that LPT performs better than a general NE. However, LPT is not the best possible approximation. In particular, we present a polynomial time approximation scheme (PTAS) for the makespan minimization problem which provides a schedule with IR_min of 1+epsilon for any given epsilon. With respect to computational complexity, we show that given an NE on m >= 3 identical machines or m >= 2 unrelated machines, it is NP-hard to determine whether a given coalition can deviate such that every member decreases its cost.
[ { "created": "Wed, 15 Jan 2014 05:42:16 GMT", "version": "v1" } ]
2014-01-16
[ [ "Feldman", "Michal", "" ], [ "Tamir", "Tami", "" ] ]
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