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1406.6764 | Thomas S. Richardson | Thomas S. Richardson | A factorization criterion for acyclic directed mixed graphs | Appears in Proceedings of the Twenty-Fifth Conference on Uncertainty
in Artificial Intelligence (UAI2009) | null | null | UAI-P-2009-PG-462-470 | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Acyclic directed mixed graphs, also known as semi-Markov models represent the
conditional independence structure induced on an observed margin by a DAG model
with latent variables. In this paper we present a factorization criterion for
these models that is equivalent to the global Markov property given by (the
natural extension of) d-separation.
| [
{
"version": "v1",
"created": "Thu, 26 Jun 2014 04:21:47 GMT"
}
] | 1,403,827,200,000 | [
[
"Richardson",
"Thomas S.",
""
]
] |
1406.6973 | Ramanathan Guha | R.V.Guha | Communicating and resolving entity references | 18 pages, 4 figures | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Statements about entities occur everywhere, from newspapers and web pages to
structured databases. Correlating references to entities across systems that
use different identifiers or names for them is a widespread problem. In this
paper, we show how shared knowledge between systems can be used to solve this
problem. We present "reference by description", a formal model for resolving
references. We provide some results on the conditions under which a randomly
chosen entity in one system can, with high probability, be mapped to the same
entity in a different system.
| [
{
"version": "v1",
"created": "Thu, 26 Jun 2014 18:25:53 GMT"
}
] | 1,403,827,200,000 | [
[
"Guha",
"R. V.",
""
]
] |
1406.7196 | Fr\'ed\'eric Lardeux | Fr\'ed\'eric Lardeux, Eric Monfroy, Broderick Crawford, Ricardo Soto | Set Constraint Model and Automated Encoding into SAT: Application to the
Social Golfer Problem | Submitted to Annals of Operations research | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | On the one hand, Constraint Satisfaction Problems allow one to declaratively
model problems. On the other hand, propositional satisfiability problem (SAT)
solvers can handle huge SAT instances. We thus present a technique to
declaratively model set constraint problems and to encode them automatically
into SAT instances. We apply our technique to the Social Golfer Problem and we
also use it to break symmetries of the problem. Our technique is simpler, more
declarative, and less error-prone than direct and improved hand modeling. The
SAT instances that we automatically generate contain less clauses than improved
hand-written instances such as in [20], and with unit propagation they also
contain less variables. Moreover, they are well-suited for SAT solvers and they
are solved faster as shown when solving difficult instances of the Social
Golfer Problem.
| [
{
"version": "v1",
"created": "Fri, 27 Jun 2014 14:37:12 GMT"
},
{
"version": "v2",
"created": "Mon, 30 Jun 2014 19:23:45 GMT"
}
] | 1,404,172,800,000 | [
[
"Lardeux",
"Frédéric",
""
],
[
"Monfroy",
"Eric",
""
],
[
"Crawford",
"Broderick",
""
],
[
"Soto",
"Ricardo",
""
]
] |
1407.1041 | Florentin Smarandache | Florentin Smarandache | n-Valued Refined Neutrosophic Logic and Its Applications to Physics | 9 pages | Progress in Physics, 143-146, Vol. 4, 2013 | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this paper we present a short history of logics: from particular cases of
2-symbol or numerical valued logic to the general case of n-symbol or numerical
valued logic. We show generalizations of 2-valued Boolean logic to fuzzy logic,
also from the Kleene and Lukasiewicz 3-symbol valued logics or Belnap 4-symbol
valued logic to the most general n-symbol or numerical valued refined
neutrosophic logic. Two classes of neutrosophic norm (n-norm) and neutrosophic
conorm (n-conorm) are defined. Examples of applications of neutrosophic logic
to physics are listed in the last section. Similar generalizations can be done
for n-Valued Refined Neutrosophic Set, and respectively n- Valued Refined
Neutrosopjhic Probability.
| [
{
"version": "v1",
"created": "Thu, 3 Jul 2014 15:25:52 GMT"
}
] | 1,404,691,200,000 | [
[
"Smarandache",
"Florentin",
""
]
] |
1407.2873 | Sergey Kulikov | Sergey Kulikov | Possibilities of technologization of philosophical knowledge | 6 pages, in Russian, conference "Constraction of Man" (Russia, Tomsk,
2011, April 26-29) | null | 10.13140/2.1.3036.7521 | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Article purpose is the analysis of a question of possibility of
technologization of philosophical knowledge. We understand the organization of
cognitive activity which is guided by the set of methods guaranteed bringing to
successful (i.e. to precisely corresponding set parameters) to applied results
as technologization. Transformation of sense of philosophy allows revealing
possibilities of its technologization. The leading role in this process is
played by philosophy of science which creates conditions for such
transformation. At the same time there is justified an appeal to branch
combination theory of the directions of scientific knowledge and partial
refusal of understanding of philosophy as synthetic knowledge in which the main
task is permission, instead of generation of paradoxes.
| [
{
"version": "v1",
"created": "Thu, 10 Jul 2014 17:38:13 GMT"
}
] | 1,423,440,000,000 | [
[
"Kulikov",
"Sergey",
""
]
] |
1407.3208 | Brian Ruttenberg | Brian E. Ruttenberg and Avi Pfeffer | Decision-Making with Complex Data Structures using Probabilistic
Programming | null | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Existing decision-theoretic reasoning frameworks such as decision networks
use simple data structures and processes. However, decisions are often made
based on complex data structures, such as social networks and protein
sequences, and rich processes involving those structures. We present a
framework for representing decision problems with complex data structures using
probabilistic programming, allowing probabilistic models to be created with
programming language constructs such as data structures and control flow. We
provide a way to use arbitrary data types with minimal effort from the user,
and an approximate decision-making algorithm that is effective even when the
information space is very large or infinite. Experimental results show our
algorithm working on problems with very large information spaces.
| [
{
"version": "v1",
"created": "Fri, 11 Jul 2014 16:20:15 GMT"
}
] | 1,405,296,000,000 | [
[
"Ruttenberg",
"Brian E.",
""
],
[
"Pfeffer",
"Avi",
""
]
] |
1407.3211 | Faruk Karaaslan | Faruk Karaaslan | Possibility neutrosophic soft sets with applications in decision making
and similarity measure | null | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this paper, concept of possibility neutrosophic soft set and its
operations are defined, and their properties are studied. An application of
this theory in decision making is investigated. Also a similarity measure of
two possibility neutrosophic soft sets is introduced and discussed. Finally an
application of this similarity measure is given to select suitable person for
position in a firm.
| [
{
"version": "v1",
"created": "Wed, 9 Jul 2014 22:36:56 GMT"
}
] | 1,405,296,000,000 | [
[
"Karaaslan",
"Faruk",
""
]
] |
1407.3832 | Rob Miller | Irene-Anna Diakidoy, Antonis Kakas, Loizos Michael and Rob Miller | Non-Monotonic Reasoning and Story Comprehension | null | Proceedings of the 15th International Workshop on Non-Monotonic
Reasoning (NMR 2014), Vienna, 1719 July, 2014 | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | This paper develops a Reasoning about Actions and Change framework integrated
with Default Reasoning, suitable as a Knowledge Representation and Reasoning
framework for Story Comprehension. The proposed framework, which is guided
strongly by existing knowhow from the Psychology of Reading and Comprehension,
is based on the theory of argumentation from AI. It uses argumentation to
capture appropriate solutions to the frame, ramification and qualification
problems and generalizations of these problems required for text comprehension.
In this first part of the study the work concentrates on the central problem of
integration (or elaboration) of the explicit information from the narrative in
the text with the implicit (in the readers mind) common sense world knowledge
pertaining to the topic(s) of the story given in the text. We also report on
our empirical efforts to gather background common sense world knowledge used by
humans when reading a story and to evaluate, through a prototype system, the
ability of our approach to capture both the majority and the variability of
understanding of a story by the human readers in the experiments.
| [
{
"version": "v1",
"created": "Mon, 14 Jul 2014 21:55:10 GMT"
}
] | 1,405,468,800,000 | [
[
"Diakidoy",
"Irene-Anna",
""
],
[
"Kakas",
"Antonis",
""
],
[
"Michael",
"Loizos",
""
],
[
"Miller",
"Rob",
""
]
] |
1407.3836 | David Toth | David Toth | Imparo is complete by inverse subsumption | 3 pages | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In Inverse subsumption for complete explanatory induction Yamamoto et al.
investigate which inductive logic programming systems can learn a correct
hypothesis $H$ by using the inverse subsumption instead of inverse entailment.
We prove that inductive logic programming system Imparo is complete by inverse
subsumption for learning a correct definite hypothesis $H$ wrt the definite
background theory $B$ and ground atomic examples $E$, by establishing that
there exists a connected theory $T$ for $B$ and $E$ such that $H$ subsumes $T$.
| [
{
"version": "v1",
"created": "Mon, 14 Jul 2014 22:21:22 GMT"
}
] | 1,405,468,800,000 | [
[
"Toth",
"David",
""
]
] |
1407.4234 | Emil Weydert | Emil Weydert | A Plausibility Semantics for Abstract Argumentation Frameworks | Proceedings of the 15th International Workshop on Non-Monotonic
Reasoning (NMR 2014). This is an improved and extended version of the
author's ECSQARU 2013 paper | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We propose and investigate a simple ranking-measure-based extension semantics
for abstract argumentation frameworks based on their generic instantiation by
default knowledge bases and the ranking construction semantics for default
reasoning. In this context, we consider the path from structured to logical to
shallow semantic instantiations. The resulting well-justified JZ-extension
semantics diverges from more traditional approaches.
| [
{
"version": "v1",
"created": "Wed, 16 Jul 2014 08:53:36 GMT"
}
] | 1,405,555,200,000 | [
[
"Weydert",
"Emil",
""
]
] |
1407.4364 | Muhammad Marwan Muhammad Fuad | Muhammad Marwan Muhammad Fuad | One-Step or Two-Step Optimization and the Overfitting Phenomenon: A Case
Study on Time Series Classification | null | Proceedings of the 6th International Conference on Agents and
Artificial Intelligence -6 - 8 March, 2014 | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | For the last few decades, optimization has been developing at a fast rate.
Bio-inspired optimization algorithms are metaheuristics inspired by nature.
These algorithms have been applied to solve different problems in engineering,
economics, and other domains. Bio-inspired algorithms have also been applied in
different branches of information technology such as networking and software
engineering. Time series data mining is a field of information technology that
has its share of these applications too. In previous works we showed how
bio-inspired algorithms such as the genetic algorithms and differential
evolution can be used to find the locations of the breakpoints used in the
symbolic aggregate approximation of time series representation, and in another
work we showed how we can utilize the particle swarm optimization, one of the
famous bio-inspired algorithms, to set weights to the different segments in the
symbolic aggregate approximation representation. In this paper we present, in
two different approaches, a new meta optimization process that produces optimal
locations of the breakpoints in addition to optimal weights of the segments.
The experiments of time series classification task that we conducted show an
interesting example of how the overfitting phenomenon, a frequently encountered
problem in data mining which happens when the model overfits the training set,
can interfere in the optimization process and hide the superior performance of
an optimization algorithm.
| [
{
"version": "v1",
"created": "Wed, 16 Jul 2014 16:12:16 GMT"
}
] | 1,405,555,200,000 | [
[
"Fuad",
"Muhammad Marwan Muhammad",
""
]
] |
1407.4709 | Vadim Bulitko | Vadim Bulitko | Flow for Meta Control | null | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The psychological state of flow has been linked to optimizing human
performance. A key condition of flow emergence is a match between the human
abilities and complexity of the task. We propose a simple computational model
of flow for Artificial Intelligence (AI) agents. The model factors the standard
agent-environment state into a self-reflective set of the agent's abilities and
a socially learned set of the environmental complexity. Maximizing the flow
serves as a meta control for the agent. We show how to apply the meta-control
policy to a broad class of AI control policies and illustrate our approach with
a specific implementation. Results in a synthetic testbed are promising and
open interesting directions for future work.
| [
{
"version": "v1",
"created": "Thu, 17 Jul 2014 15:31:03 GMT"
}
] | 1,405,641,600,000 | [
[
"Bulitko",
"Vadim",
""
]
] |
1407.5380 | Dongmo Zhang | Dongmo Zhang and Michael Thielsher | Representing and Reasoning about Game Strategies | null | null | null | null | cs.AI | http://creativecommons.org/licenses/by-nc-sa/3.0/ | As a contribution to the challenge of building game-playing AI systems, we
develop and analyse a formal language for representing and reasoning about
strategies. Our logical language builds on the existing general Game
Description Language (GDL) and extends it by a standard modality for linear
time along with two dual connectives to express preferences when combining
strategies. The semantics of the language is provided by a standard
state-transition model. As such, problems that require reasoning about games
can be solved by the standard methods for reasoning about actions and change.
We also endow the language with a specific semantics by which strategy formulas
are understood as move recommendations for a player. To illustrate how our
formalism supports automated reasoning about strategies, we demonstrate two
example methods of implementation\/: first, we formalise the semantic
interpretation of our language in conjunction with game rules and strategy
rules in the Situation Calculus; second, we show how the reasoning problem can
be solved with Answer Set Programming.
| [
{
"version": "v1",
"created": "Mon, 21 Jul 2014 06:15:27 GMT"
}
] | 1,405,987,200,000 | [
[
"Zhang",
"Dongmo",
""
],
[
"Thielsher",
"Michael",
""
]
] |
1407.6090 | arXiv Admin | Jyoti Chaturvedi, Anubha Parashar, Amrita A Manjrekar, Vinay S Bhaskar | Social and Business Intelligence Analysis Using PSO | This article has been withdrawn by arXiv administrators due to
disputed authorship | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The goal of this paper is to elaborate swarm intelligence for business
intelligence decision making and the business rules management improvement.
.The swarm optimization, which is highly influenced by the behavior of
creature, performs in group. The Spatial data is defined as data that is
represented by 2D or 3D images. SQL Server supports only 2D images till now. As
we know that location is an essential part of any organizational data as well
as business data enterprises maintain customer address lists, own property,
ship goods from and to warehouses, manage transport flows among their
workforce, and perform many other activities. By means to say a lot of spatial
data is used and processed by enterprises, organizations and other bodies in
order to make the things more visible and self descriptive. From the
experiments, we found that PSO is can facilitate the intelligence in social and
business behavior.
| [
{
"version": "v1",
"created": "Wed, 23 Jul 2014 02:14:48 GMT"
},
{
"version": "v2",
"created": "Thu, 25 Aug 2016 16:24:39 GMT"
}
] | 1,472,169,600,000 | [
[
"Chaturvedi",
"Jyoti",
""
],
[
"Parashar",
"Anubha",
""
],
[
"Manjrekar",
"Amrita A",
""
],
[
"Bhaskar",
"Vinay S",
""
]
] |
1407.6166 | Evgeniy Vodolazskiy | Michail Schlesinger, Boris Flach, Evgeniy Vodolazskiy | M-best solutions for a class of fuzzy constraint satisfaction problems | 9 pages | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The article considers one of the possible generalizations of constraint
satisfaction problems where relations are replaced by multivalued membership
functions. In this case operations of disjunction and conjunction are replaced
by maximum and minimum, and consistency of a solution becomes multivalued
rather than binary. The article studies the problem of finding d most
admissible solutions for a given d. A tractable subclass of these problems is
defined by the concepts of invariants and polymorphisms similar to the classic
constraint satisfaction approach. These concepts are adapted in two ways.
Firstly, the correspondence of "invariant-polymorphism" is generalized to
(min,max) semirings. Secondly, we consider non-uniform polymorphisms, where
each variable has its own operator, in contrast to the case of one operator
common for all variables. The article describes an algorithm that finds $d$
most admissible solutions in polynomial time, provided that the problem is
invariant with respect to some non-uniform majority operator. It is essential
that this operator needs not to be known for the algorithm to work. Moreover,
even a guarantee for the existence of such an operator is not necessary. The
algorithm either finds the solution or discards the problem. The latter is
possible only if the problem has no majority polymorphism.
| [
{
"version": "v1",
"created": "Wed, 23 Jul 2014 10:48:09 GMT"
}
] | 1,406,160,000,000 | [
[
"Schlesinger",
"Michail",
""
],
[
"Flach",
"Boris",
""
],
[
"Vodolazskiy",
"Evgeniy",
""
]
] |
1407.6699 | Eduardo Vega-Fuentes | Eduardo Vega-Fuentes, Juan Manuel Cerezo-Sanchez, Sonia Leon-del
Rosario and Aurelio Vega-Martinez | Fuzzy inference system for integrated VVC in isolated power systems | arXiv admin note: substantial text overlap with arXiv:1401.1632 | International Journal of Artificial Intelligence & Aplications,
(IJAIA), January 2014, Volume 5, Number 1, pp 91-106 | 10.5121/ijaia.2014.5107 | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | This paper presents a fuzzy inference system for integrated volt/var control
(VVC) in distribution substations. The purpose is go forward to automation
distribution applying conservation voltage reduction (CVR) in isolated power
systems where control capabilities are limited. A fuzzy controller has been
designed. Working as an on-line tool, it has been tested under real conditions
and it has managed the operation during a whole day in a distribution
substation. Within the limits of control capabilities of the system, the
controller maintained successfully an acceptable voltage profile, power factor
values over 0,98 and it has ostensibly improved the performance given by an
optimal power flow based automation system. CVR savings during the test are
evaluated and the aim to integrate it in the VVC is presented.
| [
{
"version": "v1",
"created": "Mon, 10 Feb 2014 12:30:47 GMT"
}
] | 1,406,246,400,000 | [
[
"Vega-Fuentes",
"Eduardo",
""
],
[
"Cerezo-Sanchez",
"Juan Manuel",
""
],
[
"Rosario",
"Sonia Leon-del",
""
],
[
"Vega-Martinez",
"Aurelio",
""
]
] |
1407.6885 | Marie-Laure Mugnier | Jean-Francois Baget, Fabien Garreau, Marie-Laure Mugnier, Swan Rocher | Extending Acyclicity Notions for Existential Rules (\emph{long version}) | This report contains a revised version (July 2014) of the paper that
will appear in the proceedings of ECAI 2014 and an appendix with proofs that
could not be included in the paper for space restriction reasons | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Existential rules have been proposed for representing ontological knowledge,
specifically in the context of Ontology-Based Query Answering. Entailment with
existential rules is undecidable. We focus in this paper on conditions that
ensure the termination of a breadth-first forward chaining algorithm known as
the chase. First, we propose a new tool that allows to extend existing
acyclicity conditions ensuring chase termination, while keeping good complexity
properties. Second, we consider the extension to existential rules with
nonmonotonic negation under stable model semantics and further extend
acyclicity results obtained in the positive case.
| [
{
"version": "v1",
"created": "Fri, 25 Jul 2014 13:27:34 GMT"
}
] | 1,406,505,600,000 | [
[
"Baget",
"Jean-Francois",
""
],
[
"Garreau",
"Fabien",
""
],
[
"Mugnier",
"Marie-Laure",
""
],
[
"Rocher",
"Swan",
""
]
] |
1407.7008 | Lorenzo Livi | Enrico De Santis, Lorenzo Livi, Alireza Sadeghian, Antonello Rizzi | Modeling and Recognition of Smart Grid Faults by a Combined Approach of
Dissimilarity Learning and One-Class Classification | null | null | 10.1016/j.neucom.2015.05.112 | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Detecting faults in electrical power grids is of paramount importance, either
from the electricity operator and consumer viewpoints. Modern electric power
grids (smart grids) are equipped with smart sensors that allow to gather
real-time information regarding the physical status of all the component
elements belonging to the whole infrastructure (e.g., cables and related
insulation, transformers, breakers and so on). In real-world smart grid
systems, usually, additional information that are related to the operational
status of the grid itself are collected such as meteorological information.
Designing a suitable recognition (discrimination) model of faults in a
real-world smart grid system is hence a challenging task. This follows from the
heterogeneity of the information that actually determine a typical fault
condition. The second point is that, for synthesizing a recognition model, in
practice only the conditions of observed faults are usually meaningful.
Therefore, a suitable recognition model should be synthesized by making use of
the observed fault conditions only. In this paper, we deal with the problem of
modeling and recognizing faults in a real-world smart grid system, which
supplies the entire city of Rome, Italy. Recognition of faults is addressed by
following a combined approach of multiple dissimilarity measures customization
and one-class classification techniques. We provide here an in-depth study
related to the available data and to the models synthesized by the proposed
one-class classifier. We offer also a comprehensive analysis of the fault
recognition results by exploiting a fuzzy set based reliability decision rule.
| [
{
"version": "v1",
"created": "Fri, 25 Jul 2014 19:15:25 GMT"
},
{
"version": "v2",
"created": "Wed, 17 Dec 2014 15:46:26 GMT"
}
] | 1,435,708,800,000 | [
[
"De Santis",
"Enrico",
""
],
[
"Livi",
"Lorenzo",
""
],
[
"Sadeghian",
"Alireza",
""
],
[
"Rizzi",
"Antonello",
""
]
] |
1407.7138 | Lorenzo Livi | Lorenzo Livi, Alireza Sadeghian | Data granulation by the principles of uncertainty | 16 pages, 9 figures, 52 references | null | 10.1016/j.patrec.2015.04.008 | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Researches in granular modeling produced a variety of mathematical models,
such as intervals, (higher-order) fuzzy sets, rough sets, and shadowed sets,
which are all suitable to characterize the so-called information granules.
Modeling of the input data uncertainty is recognized as a crucial aspect in
information granulation. Moreover, the uncertainty is a well-studied concept in
many mathematical settings, such as those of probability theory, fuzzy set
theory, and possibility theory. This fact suggests that an appropriate
quantification of the uncertainty expressed by the information granule model
could be used to define an invariant property, to be exploited in practical
situations of information granulation. In this perspective, a procedure of
information granulation is effective if the uncertainty conveyed by the
synthesized information granule is in a monotonically increasing relation with
the uncertainty of the input data. In this paper, we present a data granulation
framework that elaborates over the principles of uncertainty introduced by
Klir. Being the uncertainty a mesoscopic descriptor of systems and data, it is
possible to apply such principles regardless of the input data type and the
specific mathematical setting adopted for the information granules. The
proposed framework is conceived (i) to offer a guideline for the synthesis of
information granules and (ii) to build a groundwork to compare and
quantitatively judge over different data granulation procedures. To provide a
suitable case study, we introduce a new data granulation technique based on the
minimum sum of distances, which is designed to generate type-2 fuzzy sets. We
analyze the procedure by performing different experiments on two distinct data
types: feature vectors and labeled graphs. Results show that the uncertainty of
the input data is suitably conveyed by the generated type-2 fuzzy set models.
| [
{
"version": "v1",
"created": "Sat, 26 Jul 2014 16:03:13 GMT"
},
{
"version": "v2",
"created": "Mon, 15 Sep 2014 14:42:35 GMT"
},
{
"version": "v3",
"created": "Sun, 11 Jan 2015 18:57:41 GMT"
},
{
"version": "v4",
"created": "Mon, 2 Mar 2015 13:46:50 GMT"
}
] | 1,430,352,000,000 | [
[
"Livi",
"Lorenzo",
""
],
[
"Sadeghian",
"Alireza",
""
]
] |
1407.7180 | Joseph Y. Halpern | Joseph Y. Halpern | Defining Relative Likelihood in Partially-Ordered Preferential
Structures | Appears in Proceedings of the Twelfth Conference on Uncertainty in
Artificial Intelligence (UAI1996) | null | null | UAI-P-1996-PG-299-306 | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Starting with a likelihood or preference order on worlds, we extend it to a
likelihood ordering on sets of worlds in a natural way, and examine the
resulting logic. Lewis (1973) earlier considered such a notion of relative
likelihood in the context of studying counterfactuals, but he assumed a total
preference order on worlds. Complications arise when examining partial orders
that are not present for total orders. There are subtleties involving the exact
approach to lifting the order on worlds to an order on sets of worlds. In
addition, the axiomatization of the logic of relative likelihood in the case of
partial orders gives insight into the connection between relative likelihood
and default reasoning.
| [
{
"version": "v1",
"created": "Sun, 27 Jul 2014 05:16:18 GMT"
}
] | 1,406,592,000,000 | [
[
"Halpern",
"Joseph Y.",
""
]
] |
1407.7182 | Joseph Y. Halpern | Joseph Y. Halpern | Conditional Plausibility Measures and Bayesian Networks | Appears in Proceedings of the Sixteenth Conference on Uncertainty in
Artificial Intelligence (UAI2000) | null | null | UAI-P-2000-PG-247-255 | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | A general notion of algebraic conditional plausibility measures is defined.
Probability measures, ranking functions, possibility measures, and (under the
appropriate definitions) sets of probability measures can all be viewed as
defining algebraic conditional plausibility measures. It is shown that the
technology of Bayesian networks can be applied to algebraic conditional
plausibility measures.
| [
{
"version": "v1",
"created": "Sun, 27 Jul 2014 05:24:44 GMT"
}
] | 1,406,592,000,000 | [
[
"Halpern",
"Joseph Y.",
""
]
] |
1407.7183 | Peter D Grunwald | Peter D. Grunwald, Joseph Y. Halpern | Updating Probabilities | Appears in Proceedings of the Eighteenth Conference on Uncertainty in
Artificial Intelligence (UAI2002) | null | null | UAI-P-2002-PG-187-196 | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | As examples such as the Monty Hall puzzle show, applying conditioning to
update a probability distribution on a ``naive space', which does not take into
account the protocol used, can often lead to counterintuitive results. Here we
examine why. A criterion known as CAR (coarsening at random) in the statistical
literature characterizes when ``naive' conditioning in a naive space works. We
show that the CAR condition holds rather infrequently. We then consider more
generalized notions of update such as Jeffrey conditioning and minimizing
relative entropy (MRE). We give a generalization of the CAR condition that
characterizes when Jeffrey conditioning leads to appropriate answers, but show
that there are no such conditions for MRE. This generalizes and interconnects
previous results obtained in the literature on CAR and MRE.
| [
{
"version": "v1",
"created": "Sun, 27 Jul 2014 05:25:17 GMT"
}
] | 1,406,592,000,000 | [
[
"Grunwald",
"Peter D.",
""
],
[
"Halpern",
"Joseph Y.",
""
]
] |
1407.7184 | Joseph Y. Halpern | Joseph Y. Halpern, Riccardo Pucella | Reasoning about Expectation | Appears in Proceedings of the Eighteenth Conference on Uncertainty in
Artificial Intelligence (UAI2002) | null | null | UAI-P-2002-PG-207-215 | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Expectation is a central notion in probability theory. The notion of
expectation also makes sense for other notions of uncertainty. We introduce a
propositional logic for reasoning about expectation, where the semantics
depends on the underlying representation of uncertainty. We give sound and
complete axiomatizations for the logic in the case that the underlying
representation is (a) probability, (b) sets of probability measures, (c) belief
functions, and (d) possibility measures. We show that this logic is more
expressive than the corresponding logic for reasoning about likelihood in the
case of sets of probability measures, but equi-expressive in the case of
probability, belief, and possibility. Finally, we show that satisfiability for
these logics is NP-complete, no harder than satisfiability for propositional
logic.
| [
{
"version": "v1",
"created": "Sun, 27 Jul 2014 05:25:25 GMT"
}
] | 1,406,592,000,000 | [
[
"Halpern",
"Joseph Y.",
""
],
[
"Pucella",
"Riccardo",
""
]
] |
1407.7185 | Joseph Y. Halpern | Joseph Y. Halpern, Riccardo Pucella | A Logic for Reasoning about Evidence | Appears in Proceedings of the Nineteenth Conference on Uncertainty in
Artificial Intelligence (UAI2003) | null | null | UAI-P-2003-PG-297-304 | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We introduce a logic for reasoning about evidence, that essentially views
evidence as a function from prior beliefs (before making an observation) to
posterior beliefs (after making the observation). We provide a sound and
complete axiomatization for the logic, and consider the complexity of the
decision problem. Although the reasoning in the logic is mainly propositional,
we allow variables representing numbers and quantification over them. This
expressive power seems necessary to capture important properties of evidence
| [
{
"version": "v1",
"created": "Sun, 27 Jul 2014 05:25:52 GMT"
}
] | 1,406,592,000,000 | [
[
"Halpern",
"Joseph Y.",
""
],
[
"Pucella",
"Riccardo",
""
]
] |
1407.7188 | Peter D Grunwald | Peter D. Grunwald, Joseph Y. Halpern | When Ignorance is Bliss | Appears in Proceedings of the Twentieth Conference on Uncertainty in
Artificial Intelligence (UAI2004) | null | null | UAI-P-2004-PG-226-234 | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | It is commonly-accepted wisdom that more information is better, and that
information should never be ignored. Here we argue, using both a Bayesian and a
non-Bayesian analysis, that in some situations you are better off ignoring
information if your uncertainty is represented by a set of probability
measures. These include situations in which the information is relevant for the
prediction task at hand. In the non-Bayesian analysis, we show how ignoring
information avoids dilation, the phenomenon that additional pieces of
information sometimes lead to an increase in uncertainty. In the Bayesian
analysis, we show that for small sample sizes and certain prediction tasks, the
Bayesian posterior based on a noninformative prior yields worse predictions
than simply ignoring the given information.
| [
{
"version": "v1",
"created": "Sun, 27 Jul 2014 05:34:39 GMT"
}
] | 1,406,592,000,000 | [
[
"Grunwald",
"Peter D.",
""
],
[
"Halpern",
"Joseph Y.",
""
]
] |
1407.7189 | Joseph Y. Halpern | Joseph Y. Halpern, Riccardo Pucella | Evidence with Uncertain Likelihoods | Appears in Proceedings of the Twenty-First Conference on Uncertainty
in Artificial Intelligence (UAI2005) | null | null | UAI-P-2005-PG-243-250 | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | An agent often has a number of hypotheses, and must choose among them based
on observations, or outcomes of experiments. Each of these observations can be
viewed as providing evidence for or against various hypotheses. All the
attempts to formalize this intuition up to now have assumed that associated
with each hypothesis h there is a likelihood function {\mu}h, which is a
probability measure that intuitively describes how likely each observation is,
conditional on h being the correct hypothesis. We consider an extension of this
framework where there is uncertainty as to which of a number of likelihood
functions is appropriate, and discuss how one formal approach to defining
evidence, which views evidence as a function from priors to posteriors, can be
generalized to accommodate this uncertainty.
| [
{
"version": "v1",
"created": "Sun, 27 Jul 2014 05:35:44 GMT"
}
] | 1,406,592,000,000 | [
[
"Halpern",
"Joseph Y.",
""
],
[
"Pucella",
"Riccardo",
""
]
] |
1407.7190 | Peter D Grunwald | Peter D. Grunwald, Joseph Y. Halpern | A Game-Theoretic Analysis of Updating Sets of Probabilities | Appears in Proceedings of the Twenty-Fourth Conference on Uncertainty
in Artificial Intelligence (UAI2008) | null | null | UAI-P-2008-PG-240-247 | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We consider how an agent should update her uncertainty when it is represented
by a set P of probability distributions and the agent observes that a random
variable X takes on value x, given that the agent makes decisions using the
minimax criterion, perhaps the best-studied and most commonly-used criterion in
the literature. We adopt a game-theoretic framework, where the agent plays
against a bookie, who chooses some distribution from P. We consider two
reasonable games that differ in what the bookie knows when he makes his choice.
Anomalies that have been observed before, like time inconsistency, can be
understood as arising because different games are being played, against bookies
with different information. We characterize the important special cases in
which the optimal decision rules according to the minimax criterion amount to
either conditioning or simply ignoring the information. Finally, we consider
the relationship between conditioning and calibration when uncertainty is
described by sets of probabilities.
| [
{
"version": "v1",
"created": "Sun, 27 Jul 2014 05:37:10 GMT"
}
] | 1,406,592,000,000 | [
[
"Grunwald",
"Peter D.",
""
],
[
"Halpern",
"Joseph Y.",
""
]
] |
1407.7191 | Joseph Y. Halpern | Joseph Y. Halpern, Nan Rong, Ashutosh Saxena | MDPs with Unawareness | Appears in Proceedings of the Twenty-Sixth Conference on Uncertainty
in Artificial Intelligence (UAI2010) | null | null | UAI-P-2010-PG-228-235 | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Markov decision processes (MDPs) are widely used for modeling decision-making
problems in robotics, automated control, and economics. Traditional MDPs assume
that the decision maker (DM) knows all states and actions. However, this may
not be true in many situations of interest. We define a new framework, MDPs
with unawareness (MDPUs) to deal with the possibilities that a DM may not be
aware of all possible actions. We provide a complete characterization of when a
DM can learn to play near-optimally in an MDPU, and give an algorithm that
learns to play near-optimally when it is possible to do so, as efficiently as
possible. In particular, we characterize when a near-optimal solution can be
found in polynomial time.
| [
{
"version": "v1",
"created": "Sun, 27 Jul 2014 05:37:48 GMT"
}
] | 1,406,592,000,000 | [
[
"Halpern",
"Joseph Y.",
""
],
[
"Rong",
"Nan",
""
],
[
"Saxena",
"Ashutosh",
""
]
] |
1407.7281 | Eric J. Horvitz | Eric J. Horvitz, David Heckerman | Modular Belief Updates and Confusion about Measures of Certainty in
Artificial Intelligence Research | Appears in Proceedings of the First Conference on Uncertainty in
Artificial Intelligence (UAI1985) | null | null | UAI-P-1985-PG-283-286 | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Over the last decade, there has been growing interest in the use or measures
or change in belief for reasoning with uncertainty in artificial intelligence
research. An important characteristic of several methodologies that reason with
changes in belief or belief updates, is a property that we term modularity. We
call updates that satisfy this property modular updates. Whereas probabilistic
measures of belief update - which satisfy the modularity property were first
discovered in the nineteenth century, knowledge and discussion of these
quantities remains obscure in artificial intelligence research. We define
modular updates and discuss their inappropriate use in two influential expert
systems.
| [
{
"version": "v1",
"created": "Sun, 27 Jul 2014 20:37:36 GMT"
}
] | 1,406,592,000,000 | [
[
"Horvitz",
"Eric J.",
""
],
[
"Heckerman",
"David",
""
]
] |
1407.7933 | EPTCS | Steffen Ziegert (University of Paderborn) | Graph Transformation Planning via Abstraction | In Proceedings GRAPHITE 2014, arXiv:1407.7671 | EPTCS 159, 2014, pp. 71-83 | 10.4204/EPTCS.159.7 | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Modern software systems increasingly incorporate self-* behavior to adapt to
changes in the environment at runtime. Such adaptations often involve
reconfiguring the software architecture of the system. Many systems also need
to manage their architecture themselves, i.e., they need a planning component
to autonomously decide which reconfigurations to execute to reach a desired
target configuration. For the specification of reconfigurations, we employ
graph transformations systems (GTS) due to the close relation of graphs and UML
object diagrams. We solve the resulting planning problems with a planning
system that works directly on a GTS. It features a domain-independent heuristic
that uses the solution length of an abstraction of the original problem as an
estimate. Finally, we provide experimental results on two different domains,
which confirm that our heuristic performs better than another
domain-independent heuristic which resembles heuristics employed in related
work.
| [
{
"version": "v1",
"created": "Wed, 30 Jul 2014 03:23:24 GMT"
}
] | 1,406,764,800,000 | [
[
"Ziegert",
"Steffen",
"",
"University of Paderborn"
]
] |
1407.7934 | EPTCS | Valerio Senni, Michele Stawowy (IMT Institute for Advanced Studies) | Backwards State-space Reduction for Planning in Dynamic Knowledge Bases | In Proceedings GRAPHITE 2014, arXiv:1407.7671 | EPTCS 159, 2014, pp. 84-99 | 10.4204/EPTCS.159.8 | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this paper we address the problem of planning in rich domains, where
knowledge representation is a key aspect for managing the complexity and size
of the planning domain. We follow the approach of Description Logic (DL) based
Dynamic Knowledge Bases, where a state of the world is represented concisely by
a (possibly changing) ABox and a (fixed) TBox containing the axioms, and
actions that allow to change the content of the ABox. The plan goal is given in
terms of satisfaction of a DL query. In this paper we start from a traditional
forward planning algorithm and we propose a much more efficient variant by
combining backward and forward search. In particular, we propose a Backward
State-space Reduction technique that consists in two phases: first, an Abstract
Planning Graph P is created by using the Abstract Backward Planning Algorithm
(ABP), then the abstract planning graph P is instantiated into a corresponding
planning graph P by using the Forward Plan Instantiation Algorithm (FPI). The
advantage is that in the preliminary ABP phase we produce a symbolic plan that
is a pattern to direct the search of the concrete plan. This can be seen as a
kind of informed search where the preliminary backward phase is useful to
discover properties of the state-space that can be used to direct the
subsequent forward phase. We evaluate the effectiveness of our ABP+FPI
algorithm in the reduction of the explored planning domain by comparing it to a
standard forward planning algorithm and applying both of them to a concrete
business case study.
| [
{
"version": "v1",
"created": "Wed, 30 Jul 2014 03:28:15 GMT"
}
] | 1,406,764,800,000 | [
[
"Senni",
"Valerio",
"",
"IMT Institute for Advanced Studies"
],
[
"Stawowy",
"Michele",
"",
"IMT Institute for Advanced Studies"
]
] |
1408.0032 | G\'abor Etele G\'evay | G\'abor E. G\'evay, G\'abor Danner | Calculating Ultra-Strong and Extended Solutions for Nine Men's Morris,
Morabaraba, and Lasker | (c) 2015 IEEE. Personal use of this material is permitted. Permission
from IEEE must be obtained for all other users, including
reprinting/republishing this material for advertising or promotional
purposes, creating new collective works for resale or redistribution to
servers or lists, or reuse of any copyrighted components of this work in
other works | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The strong solutions of Nine Men's Morris and its variant, Lasker Morris are
well-known results (the starting positions are draws). We re-examined both of
these games, and calculated extended strong solutions for them. By this we mean
the game-theoretic values of all possible game states that could be reached
from certain starting positions where the number of stones to be placed by the
players is different from the standard rules. These were also calculated for a
previously unsolved third variant, Morabaraba, with interesting results: most
of the starting positions where the players can place an equal number of stones
(including the standard starting position) are wins for the first player (as
opposed to the above games, where these are usually draws).
We also developed a multi-valued retrograde analysis, and used it as a basis
for an algorithm for solving these games ultra-strongly. This means that when
our program is playing against a fallible opponent, it has a greater chance of
achieving a better result than the game-theoretic value, compared to randomly
selecting between "just strongly" optimal moves. Previous attempts on
ultra-strong solutions used local heuristics or learning during games, but we
incorporated our algorithm into the retrograde analysis.
| [
{
"version": "v1",
"created": "Thu, 31 Jul 2014 21:38:05 GMT"
},
{
"version": "v2",
"created": "Sun, 15 Mar 2015 00:09:41 GMT"
}
] | 1,426,550,400,000 | [
[
"Gévay",
"Gábor E.",
""
],
[
"Danner",
"Gábor",
""
]
] |
1408.0595 | T.R. Gopalakrishnan Nair | T. R. Gopalakrishnan Nair and Meenakshi Malhotra | Correlating and Cross-linking Knowledge Threads in Informledge System
for Creating New Knowledge | 6 pages, 6 figures, 3 tables, International Conference on Knowledge
Engineering and Ontology Development, 2012 | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | There has been a considerable advance in computing, to mimic the way in which
the brain tries to comprehend and structure the information to retrieve
meaningful knowledge. It is identified that neuronal entities hold whole of the
knowledge that the species makes use of. We intended to develop a modified
knowledge based system, termed as Informledge System (ILS) with autonomous
nodes and intelligent links that integrate and structure the pieces of
knowledge. We conceive that every piece of knowledge is a cluster of
cross-linked and correlated structure. In this paper, we put forward the theory
of the nodes depicting concepts, referred as Entity Concept State which in turn
is dealt with Concept State Diagrams (CSD). This theory is based on an abstract
framework provided by the concepts. The framework represents the ILS as the
weighted graph where the weights attached with the linked nodes help in
knowledge retrieval by providing the direction of connectivity of autonomous
nodes present in knowledge thread traversal. Here for the first time in the
process of developing Informledge, we apply tenor computation for creating
intelligent combinatorial knowledge with cross mutation to create fresh
knowledge which looks to be the fundamentals of a typical thought process.
| [
{
"version": "v1",
"created": "Mon, 4 Aug 2014 06:10:24 GMT"
}
] | 1,407,196,800,000 | [
[
"Nair",
"T. R. Gopalakrishnan",
""
],
[
"Malhotra",
"Meenakshi",
""
]
] |
1408.0651 | Matteo Brunelli | Matteo Brunelli and Michele Fedrizzi | Boundary properties of the inconsistency of pairwise comparisons in
group decisions | 21 pages, 6 figures | European Journal of Operational Research, 240(3), 765-773, 2015 | 10.1016/j.ejor.2014.07.045 | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | This paper proposes an analysis of the effects of consensus and preference
aggregation on the consistency of pairwise comparisons. We define some boundary
properties for the inconsistency of group preferences and investigate their
relation with different inconsistency indices. Some results are presented on
more general dependencies between properties of inconsistency indices and the
satisfaction of boundary properties. In the end, given three boundary
properties and nine indices among the most relevant ones, we will be able to
present a complete analysis of what indices satisfy what properties and offer a
reflection on the interpretation of the inconsistency of group preferences.
| [
{
"version": "v1",
"created": "Mon, 4 Aug 2014 11:45:42 GMT"
}
] | 1,459,900,800,000 | [
[
"Brunelli",
"Matteo",
""
],
[
"Fedrizzi",
"Michele",
""
]
] |
1408.1479 | Arthur L. Delcher | Arthur L. Delcher, Adam J. Grove, Simon Kasif, Judea Pearl | Logarithmic-Time Updates and Queries in Probabilistic Networks | Appears in Proceedings of the Eleventh Conference on Uncertainty in
Artificial Intelligence (UAI1995) | null | null | UAI-P-1995-PG-116-124 | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this paper we propose a dynamic data structure that supports efficient
algorithms for updating and querying singly connected Bayesian networks (causal
trees and polytrees). In the conventional algorithms, new evidence in absorbed
in time O(1) and queries are processed in time O(N), where N is the size of the
network. We propose a practical algorithm which, after a preprocessing phase,
allows us to answer queries in time O(log N) at the expense of O(logn N) time
per evidence absorption. The usefulness of sub-linear processing time manifests
itself in applications requiring (near) real-time response over large
probabilistic databases.
| [
{
"version": "v1",
"created": "Thu, 7 Aug 2014 06:22:13 GMT"
}
] | 1,407,456,000,000 | [
[
"Delcher",
"Arthur L.",
""
],
[
"Grove",
"Adam J.",
""
],
[
"Kasif",
"Simon",
""
],
[
"Pearl",
"Judea",
""
]
] |
1408.1480 | Adnan Darwiche | Adnan Darwiche, Gregory M. Provan | Query DAGs: A Practical Paradigm for Implementing Belief Network
Inference | Appears in Proceedings of the Twelfth Conference on Uncertainty in
Artificial Intelligence (UAI1996) | null | null | UAI-P-1996-PG-203-210 | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We describe a new paradigm for implementing inference in belief networks,
which relies on compiling a belief network into an arithmetic expression called
a Query DAG (Q-DAG). Each non-leaf node of a Q-DAG represents a numeric
operation, a number, or a symbol for evidence. Each leaf node of a Q-DAG
represents the answer to a network query, that is, the probability of some
event of interest. It appears that Q-DAGs can be generated using any of the
algorithms for exact inference in belief networks --- we show how they can be
generated using clustering and conditioning algorithms. The time and space
complexity of a Q-DAG generation algorithm is no worse than the time complexity
of the inference algorithm on which it is based; that of a Q-DAG on-line
evaluation algorithm is linear in the size of the Q-DAG, and such inference
amounts to a standard evaluation of the arithmetic expression it represents.
The main value of Q-DAGs is in reducing the software and hardware resources
required to utilize belief networks in on-line, real-world applications. The
proposed framework also facilitates the development of on-line inference on
different software and hardware platforms, given the simplicity of the Q-DAG
evaluation algorithm. This paper describes this new paradigm for probabilistic
inference, explaining how it works, its uses, and outlines some of the research
directions that it leads to.
| [
{
"version": "v1",
"created": "Thu, 7 Aug 2014 06:22:51 GMT"
}
] | 1,407,456,000,000 | [
[
"Darwiche",
"Adnan",
""
],
[
"Provan",
"Gregory M.",
""
]
] |
1408.1481 | Daniel Lehmann | Daniel Lehmann | Generalized Qualitative Probability: Savage Revisited | Appears in Proceedings of the Twelfth Conference on Uncertainty in
Artificial Intelligence (UAI1996) | null | null | UAI-P-1996-PG-381-388 | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Preferences among acts are analyzed in the style of L. Savage, but as
partially ordered. The rationality postulates considered are weaker than
Savage's on three counts. The Sure Thing Principle is derived in this setting.
The postulates are shown to lead to a characterization of generalized
qualitative probability that includes and blends both traditional qualitative
probability and the ranked structures used in logical approaches.
| [
{
"version": "v1",
"created": "Thu, 7 Aug 2014 06:23:08 GMT"
}
] | 1,407,456,000,000 | [
[
"Lehmann",
"Daniel",
""
]
] |
1408.1484 | Leonid Peshkin | Leonid Peshkin, Kee-Eung Kim, Nicolas Meuleau, Leslie Pack Kaelbling | Learning to Cooperate via Policy Search | Appears in Proceedings of the Sixteenth Conference on Uncertainty in
Artificial Intelligence (UAI2000) | null | null | UAI-P-2000-PG-489-496 | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Cooperative games are those in which both agents share the same payoff
structure. Value-based reinforcement-learning algorithms, such as variants of
Q-learning, have been applied to learning cooperative games, but they only
apply when the game state is completely observable to both agents. Policy
search methods are a reasonable alternative to value-based methods for
partially observable environments. In this paper, we provide a gradient-based
distributed policy-search method for cooperative games and compare the notion
of local optimum to that of Nash equilibrium. We demonstrate the effectiveness
of this method experimentally in a small, partially observable simulated soccer
domain.
| [
{
"version": "v1",
"created": "Thu, 7 Aug 2014 06:25:37 GMT"
}
] | 1,407,456,000,000 | [
[
"Peshkin",
"Leonid",
""
],
[
"Kim",
"Kee-Eung",
""
],
[
"Meuleau",
"Nicolas",
""
],
[
"Kaelbling",
"Leslie Pack",
""
]
] |
1408.1487 | Marco Zaffalon | Marco Zaffalon, Marcus Hutter | Robust Feature Selection by Mutual Information Distributions | Appears in Proceedings of the Eighteenth Conference on Uncertainty in
Artificial Intelligence (UAI2002) | null | null | UAI-P-2002-PG-577-584 | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Mutual information is widely used in artificial intelligence, in a
descriptive way, to measure the stochastic dependence of discrete random
variables. In order to address questions such as the reliability of the
empirical value, one must consider sample-to-population inferential approaches.
This paper deals with the distribution of mutual information, as obtained in a
Bayesian framework by a second-order Dirichlet prior distribution. The exact
analytical expression for the mean and an analytical approximation of the
variance are reported. Asymptotic approximations of the distribution are
proposed. The results are applied to the problem of selecting features for
incremental learning and classification of the naive Bayes classifier. A fast,
newly defined method is shown to outperform the traditional approach based on
empirical mutual information on a number of real data sets. Finally, a
theoretical development is reported that allows one to efficiently extend the
above methods to incomplete samples in an easy and effective way.
| [
{
"version": "v1",
"created": "Thu, 7 Aug 2014 06:26:42 GMT"
}
] | 1,407,456,000,000 | [
[
"Zaffalon",
"Marco",
""
],
[
"Hutter",
"Marcus",
""
]
] |
1408.1488 | Gert de Cooman | Gert de Cooman, Marco Zaffalon | Updating with incomplete observations | Appears in Proceedings of the Nineteenth Conference on Uncertainty in
Artificial Intelligence (UAI2003) | null | null | UAI-P-2003-PG-142-150 | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Currently, there is renewed interest in the problem, raised by Shafer in
1985, of updating probabilities when observations are incomplete (or
set-valued). This is a fundamental problem, and of particular interest for
Bayesian networks. Recently, Grunwald and Halpern have shown that commonly used
updating strategies fail here, except under very special assumptions. We
propose a new rule for updating probabilities with incomplete observations. Our
approach is deliberately conservative: we make no or weak assumptions about the
so-called incompleteness mechanism that produces incomplete observations. We
model our ignorance about this mechanism by a vacuous lower prevision, a tool
from the theory of imprecise probabilities, and we derive a new updating rule
using coherence arguments. In general, our rule produces lower posterior
probabilities, as well as partially determinate decisions. This is a logical
consequence of the ignorance about the incompleteness mechanism. We show how
the new rule can properly address the apparent paradox in the 'Monty Hall'
puzzle. In addition, we apply it to the classification of new evidence in
Bayesian networks constructed using expert knowledge. We provide an exact
algorithm for this task with linear-time complexity, also for multiply
connected nets.
| [
{
"version": "v1",
"created": "Thu, 7 Aug 2014 06:27:04 GMT"
}
] | 1,407,456,000,000 | [
[
"de Cooman",
"Gert",
""
],
[
"Zaffalon",
"Marco",
""
]
] |
1408.1692 | Hei Chan | Hei Chan, Adnan Darwiche | When do Numbers Really Matter? | Appears in Proceedings of the Seventeenth Conference on Uncertainty
in Artificial Intelligence (UAI2001) | null | null | UAI-P-2001-PG-65-74 | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Common wisdom has it that small distinctions in the probabilities quantifying
a Bayesian network do not matter much for the resultsof probabilistic queries.
However, one can easily develop realistic scenarios under which small
variations in network probabilities can lead to significant changes in computed
queries. A pending theoretical question is then to analytically characterize
parameter changes that do or do not matter. In this paper, we study the
sensitivity of probabilistic queries to changes in network parameters and prove
some tight bounds on the impact that such parameters can have on queries. Our
analytical results pinpoint some interesting situations under which parameter
changes do or do not matter. These results are important for knowledge
engineers as they help them identify influential network parameters. They are
also important for approximate inference algorithms that preprocessnetwork CPTs
to eliminate small distinctions in probabilities.
| [
{
"version": "v1",
"created": "Thu, 7 Aug 2014 06:26:03 GMT"
}
] | 1,407,715,200,000 | [
[
"Chan",
"Hei",
""
],
[
"Darwiche",
"Adnan",
""
]
] |
1408.2027 | Eldar Karabaev | Eldar Karabaev, Olga Skvortsova | A Heuristic Search Algorithm for Solving First-Order MDPs | Appears in Proceedings of the Twenty-First Conference on Uncertainty
in Artificial Intelligence (UAI2005) | null | null | UAI-P-2005-PG-292-299 | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We present a heuristic search algorithm for solving first-order MDPs
(FOMDPs). Our approach combines first-order state abstraction that avoids
evaluating states individually, and heuristic search that avoids evaluating all
states. Firstly, we apply state abstraction directly on the FOMDP avoiding
propositionalization. Such kind of abstraction is referred to as firstorder
state abstraction. Secondly, guided by an admissible heuristic, the search is
restricted only to those states that are reachable from the initial state. We
demonstrate the usefullness of the above techniques for solving FOMDPs on a
system, referred to as FCPlanner, that entered the probabilistic track of the
International Planning Competition (IPC'2004).
| [
{
"version": "v1",
"created": "Sat, 9 Aug 2014 05:19:23 GMT"
}
] | 1,407,801,600,000 | [
[
"Karabaev",
"Eldar",
""
],
[
"Skvortsova",
"Olga",
""
]
] |
1408.2028 | Pierre-Arnuad Coquelin | Pierre-Arnuad Coquelin, Remi Munos | Bandit Algorithms for Tree Search | Appears in Proceedings of the Twenty-Third Conference on Uncertainty
in Artificial Intelligence (UAI2007) | null | null | UAI-P-2007-PG-67-74 | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Bandit based methods for tree search have recently gained popularity when
applied to huge trees, e.g. in the game of go [6]. Their efficient exploration
of the tree enables to re- turn rapidly a good value, and improve preci- sion
if more time is provided. The UCT algo- rithm [8], a tree search method based
on Up- per Confidence Bounds (UCB) [2], is believed to adapt locally to the
effective smoothness of the tree. However, we show that UCT is
"over-optimistic" in some sense, leading to a worst-case regret that may be
very poor. We propose alternative bandit algorithms for tree search. First, a
modification of UCT us- ing a confidence sequence that scales expo- nentially
in the horizon depth is analyzed. We then consider Flat-UCB performed on the
leaves and provide a finite regret bound with high probability. Then, we
introduce and analyze a Bandit Algorithm for Smooth Trees (BAST) which takes
into account ac- tual smoothness of the rewards for perform- ing efficient
"cuts" of sub-optimal branches with high confidence. Finally, we present an
incremental tree expansion which applies when the full tree is too big
(possibly in- finite) to be entirely represented and show that with high
probability, only the optimal branches are indefinitely developed. We illus-
trate these methods on a global optimization problem of a continuous function,
given noisy values.
| [
{
"version": "v1",
"created": "Sat, 9 Aug 2014 05:21:16 GMT"
}
] | 1,407,801,600,000 | [
[
"Coquelin",
"Pierre-Arnuad",
""
],
[
"Munos",
"Remi",
""
]
] |
1408.2029 | Gert de Cooman | Gert de Cooman, Filip Hermans, Erik Quaeghebeur | Sensitivity analysis for finite Markov chains in discrete time | Appears in Proceedings of the Twenty-Fourth Conference on Uncertainty
in Artificial Intelligence (UAI2008) | null | null | UAI-P-2008-PG-129-136 | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | When the initial and transition probabilities of a finite Markov chain in
discrete time are not well known, we should perform a sensitivity analysis.
This is done by considering as basic uncertainty models the so-called credal
sets that these probabilities are known or believed to belong to, and by
allowing the probabilities to vary over such sets. This leads to the definition
of an imprecise Markov chain. We show that the time evolution of such a system
can be studied very efficiently using so-called lower and upper expectations.
We also study how the inferred credal set about the state at time n evolves as
n->infinity: under quite unrestrictive conditions, it converges to a uniquely
invariant credal set, regardless of the credal set given for the initial state.
This leads to a non-trivial generalisation of the classical Perron-Frobenius
Theorem to imprecise Markov chains.
| [
{
"version": "v1",
"created": "Sat, 9 Aug 2014 05:22:05 GMT"
}
] | 1,407,801,600,000 | [
[
"de Cooman",
"Gert",
""
],
[
"Hermans",
"Filip",
""
],
[
"Quaeghebeur",
"Erik",
""
]
] |
1408.2034 | Vicenc Gomez | Vicenc Gomez, Hilbert Kappen, Michael Chertkov | Approximate inference on planar graphs using Loop Calculus and Belief
Propagation | Appears in Proceedings of the Twenty-Fifth Conference on Uncertainty
in Artificial Intelligence (UAI2009) | null | null | UAI-P-2009-PG-195-202 | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We introduce novel results for approximate inference on planar graphical
models using the loop calculus framework. The loop calculus (Chertkov and
Chernyak, 2006b) allows to express the exact partition function Z of a
graphical model as a finite sum of terms that can be evaluated once the belief
propagation (BP) solution is known. In general, full summation over all
correction terms is intractable. We develop an algorithm for the approach
presented in Chertkov et al. (2008) which represents an efficient truncation
scheme on planar graphs and a new representation of the series in terms of
Pfaffians of matrices. We analyze in detail both the loop series and the
Pfaffian series for models with binary variables and pairwise interactions, and
show that the first term of the Pfaffian series can provide very accurate
approximations. The algorithm outperforms previous truncation schemes of the
loop series and is competitive with other state-of-the-art methods for
approximate inference.
| [
{
"version": "v1",
"created": "Sat, 9 Aug 2014 05:28:26 GMT"
}
] | 1,407,801,600,000 | [
[
"Gomez",
"Vicenc",
""
],
[
"Kappen",
"Hilbert",
""
],
[
"Chertkov",
"Michael",
""
]
] |
1408.2046 | Jie Chen | Jie Chen, Kian Hsiang Low, Colin Keng-Yan Tan, Ali Oran, Patrick
Jaillet, John Dolan, Gaurav Sukhatme | Decentralized Data Fusion and Active Sensing with Mobile Sensors for
Modeling and Predicting Spatiotemporal Traffic Phenomena | Appears in Proceedings of the Twenty-Eighth Conference on Uncertainty
in Artificial Intelligence (UAI2012) | null | null | UAI-P-2012-PG-163-173 | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The problem of modeling and predicting spatiotemporal traffic phenomena over
an urban road network is important to many traffic applications such as
detecting and forecasting congestion hotspots. This paper presents a
decentralized data fusion and active sensing (D2FAS) algorithm for mobile
sensors to actively explore the road network to gather and assimilate the most
informative data for predicting the traffic phenomenon. We analyze the time and
communication complexity of D2FAS and demonstrate that it can scale well with a
large number of observations and sensors. We provide a theoretical guarantee on
its predictive performance to be equivalent to that of a sophisticated
centralized sparse approximation for the Gaussian process (GP) model: The
computation of such a sparse approximate GP model can thus be parallelized and
distributed among the mobile sensors (in a Google-like MapReduce paradigm),
thereby achieving efficient and scalable prediction. We also theoretically
guarantee its active sensing performance that improves under various practical
environmental conditions. Empirical evaluation on real-world urban road network
data shows that our D2FAS algorithm is significantly more time-efficient and
scalable than state-oftheart centralized algorithms while achieving comparable
predictive performance.
| [
{
"version": "v1",
"created": "Sat, 9 Aug 2014 05:43:53 GMT"
}
] | 1,407,801,600,000 | [
[
"Chen",
"Jie",
""
],
[
"Low",
"Kian Hsiang",
""
],
[
"Tan",
"Colin Keng-Yan",
""
],
[
"Oran",
"Ali",
""
],
[
"Jaillet",
"Patrick",
""
],
[
"Dolan",
"John",
""
],
[
"Sukhatme",
"Gaurav",
""
]
] |
1408.2048 | Nicholas Hay | Nicholas Hay, Stuart Russell, David Tolpin, Solomon Eyal Shimony | Selecting Computations: Theory and Applications | Appears in Proceedings of the Twenty-Eighth Conference on Uncertainty
in Artificial Intelligence (UAI2012) | null | null | UAI-P-2012-PG-346-355 | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Sequential decision problems are often approximately solvable by simulating
possible future action sequences. Metalevel decision procedures have been
developed for selecting which action sequences to simulate, based on estimating
the expected improvement in decision quality that would result from any
particular simulation; an example is the recent work on using bandit algorithms
to control Monte Carlo tree search in the game of Go. In this paper we develop
a theoretical basis for metalevel decisions in the statistical framework of
Bayesian selection problems, arguing (as others have done) that this is more
appropriate than the bandit framework. We derive a number of basic results
applicable to Monte Carlo selection problems, including the first finite
sampling bounds for optimal policies in certain cases; we also provide a simple
counterexample to the intuitive conjecture that an optimal policy will
necessarily reach a decision in all cases. We then derive heuristic
approximations in both Bayesian and distribution-free settings and demonstrate
their superiority to bandit-based heuristics in one-shot decision problems and
in Go.
| [
{
"version": "v1",
"created": "Sat, 9 Aug 2014 05:46:06 GMT"
}
] | 1,407,801,600,000 | [
[
"Hay",
"Nicholas",
""
],
[
"Russell",
"Stuart",
""
],
[
"Tolpin",
"David",
""
],
[
"Shimony",
"Solomon Eyal",
""
]
] |
1408.2052 | Mathias Niepert | Mathias Niepert | Markov Chains on Orbits of Permutation Groups | Appears in Proceedings of the Twenty-Eighth Conference on Uncertainty
in Artificial Intelligence (UAI2012) | null | null | UAI-P-2012-PG-624-633 | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We present a novel approach to detecting and utilizing symmetries in
probabilistic graphical models with two main contributions. First, we present a
scalable approach to computing generating sets of permutation groups
representing the symmetries of graphical models. Second, we introduce orbital
Markov chains, a novel family of Markov chains leveraging model symmetries to
reduce mixing times. We establish an insightful connection between model
symmetries and rapid mixing of orbital Markov chains. Thus, we present the
first lifted MCMC algorithm for probabilistic graphical models. Both analytical
and empirical results demonstrate the effectiveness and efficiency of the
approach.
| [
{
"version": "v1",
"created": "Sat, 9 Aug 2014 05:49:27 GMT"
}
] | 1,407,801,600,000 | [
[
"Niepert",
"Mathias",
""
]
] |
1408.2053 | Erik J. Schlicht | Erik J. Schlicht, Ritchie Lee, David H. Wolpert, Mykel J.
Kochenderfer, Brendan Tracey | Predicting the behavior of interacting humans by fusing data from
multiple sources | Appears in Proceedings of the Twenty-Eighth Conference on Uncertainty
in Artificial Intelligence (UAI2012) | null | null | UAI-P-2012-PG-756-765 | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Multi-fidelity methods combine inexpensive low-fidelity simulations with
costly but highfidelity simulations to produce an accurate model of a system of
interest at minimal cost. They have proven useful in modeling physical systems
and have been applied to engineering problems such as wing-design optimization.
During human-in-the-loop experimentation, it has become increasingly common to
use online platforms, like Mechanical Turk, to run low-fidelity experiments to
gather human performance data in an efficient manner. One concern with these
experiments is that the results obtained from the online environment generalize
poorly to the actual domain of interest. To address this limitation, we extend
traditional multi-fidelity approaches to allow us to combine fewer data points
from high-fidelity human-in-the-loop experiments with plentiful but less
accurate data from low-fidelity experiments to produce accurate models of how
humans interact. We present both model-based and model-free methods, and
summarize the predictive performance of each method under dierent conditions.
| [
{
"version": "v1",
"created": "Sat, 9 Aug 2014 05:50:20 GMT"
}
] | 1,407,801,600,000 | [
[
"Schlicht",
"Erik J.",
""
],
[
"Lee",
"Ritchie",
""
],
[
"Wolpert",
"David H.",
""
],
[
"Kochenderfer",
"Mykel J.",
""
],
[
"Tracey",
"Brendan",
""
]
] |
1408.2056 | Sheeraz Ahmad | Sheeraz Ahmad, Angela Yu | Active Sensing as Bayes-Optimal Sequential Decision Making | Appears in Proceedings of the Twenty-Ninth Conference on Uncertainty
in Artificial Intelligence (UAI2013) | null | null | UAI-P-2013-PG-12-21 | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Sensory inference under conditions of uncertainty is a major problem in both
machine learning and computational neuroscience. An important but poorly
understood aspect of sensory processing is the role of active sensing. Here, we
present a Bayes-optimal inference and control framework for active sensing,
C-DAC (Context-Dependent Active Controller). Unlike previously proposed
algorithms that optimize abstract statistical objectives such as information
maximization (Infomax) [Butko & Movellan, 2010] or one-step look-ahead accuracy
[Najemnik & Geisler, 2005], our active sensing model directly minimizes a
combination of behavioral costs, such as temporal delay, response error, and
effort. We simulate these algorithms on a simple visual search task to
illustrate scenarios in which context-sensitivity is particularly beneficial
and optimization with respect to generic statistical objectives particularly
inadequate. Motivated by the geometric properties of the C-DAC policy, we
present both parametric and non-parametric approximations, which retain
context-sensitivity while significantly reducing computational complexity.
These approximations enable us to investigate the more complex problem
involving peripheral vision, and we notice that the difference between C-DAC
and statistical policies becomes even more evident in this scenario.
| [
{
"version": "v1",
"created": "Sat, 9 Aug 2014 05:55:58 GMT"
}
] | 1,407,801,600,000 | [
[
"Ahmad",
"Sheeraz",
""
],
[
"Yu",
"Angela",
""
]
] |
1408.2057 | Giorgos Borboudakis | Giorgos Borboudakis, Ioannis Tsamardinos | Scoring and Searching over Bayesian Networks with Causal and Associative
Priors | Appears in Proceedings of the Twenty-Ninth Conference on Uncertainty
in Artificial Intelligence (UAI2013) | null | null | UAI-P-2013-PG-102-111 | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | A significant theoretical advantage of search-and-score methods for learning
Bayesian Networks is that they can accept informative prior beliefs for each
possible network, thus complementing the data. In this paper, a method is
presented for assigning priors based on beliefs on the presence or absence of
certain paths in the true network. Such beliefs correspond to knowledge about
the possible causal and associative relations between pairs of variables. This
type of knowledge naturally arises from prior experimental and observational
data, among others. In addition, a novel search-operator is proposed to take
advantage of such prior knowledge. Experiments show that, using path beliefs
improves the learning of the skeleton, as well as the edge directions in the
network.
| [
{
"version": "v1",
"created": "Sat, 9 Aug 2014 05:56:36 GMT"
}
] | 1,407,801,600,000 | [
[
"Borboudakis",
"Giorgos",
""
],
[
"Tsamardinos",
"Ioannis",
""
]
] |
1408.2058 | Krishnendu Chatterjee | Krishnendu Chatterjee, Martin Chmelik | POMDPs under Probabilistic Semantics | Appears in Proceedings of the Twenty-Ninth Conference on Uncertainty
in Artificial Intelligence (UAI2013) | null | null | UAI-P-2013-PG-142-151 | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We consider partially observable Markov decision processes (POMDPs) with
limit-average payoff, where a reward value in the interval [0,1] is associated
to every transition, and the payoff of an infinite path is the long-run average
of the rewards. We consider two types of path constraints: (i) quantitative
constraint defines the set of paths where the payoff is at least a given
threshold lambda_1 in (0,1]; and (ii) qualitative constraint which is a special
case of quantitative constraint with lambda_1=1. We consider the computation of
the almost-sure winning set, where the controller needs to ensure that the path
constraint is satisfied with probability 1. Our main results for qualitative
path constraint are as follows: (i) the problem of deciding the existence of a
finite-memory controller is EXPTIME-complete; and (ii) the problem of deciding
the existence of an infinite-memory controller is undecidable. For quantitative
path constraint we show that the problem of deciding the existence of a
finite-memory controller is undecidable.
| [
{
"version": "v1",
"created": "Sat, 9 Aug 2014 05:57:38 GMT"
}
] | 1,407,801,600,000 | [
[
"Chatterjee",
"Krishnendu",
""
],
[
"Chmelik",
"Martin",
""
]
] |
1408.2063 | Joris Mooij | Joris Mooij, Dominik Janzing, Bernhard Schoelkopf | From Ordinary Differential Equations to Structural Causal Models: the
deterministic case | Appears in Proceedings of the Twenty-Ninth Conference on Uncertainty
in Artificial Intelligence (UAI2013) | null | null | UAI-P-2013-PG-440-448 | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We show how, and under which conditions, the equilibrium states of a
first-order Ordinary Differential Equation (ODE) system can be described with a
deterministic Structural Causal Model (SCM). Our exposition sheds more light on
the concept of causality as expressed within the framework of Structural Causal
Models, especially for cyclic models.
| [
{
"version": "v1",
"created": "Sat, 9 Aug 2014 06:02:27 GMT"
}
] | 1,407,801,600,000 | [
[
"Mooij",
"Joris",
""
],
[
"Janzing",
"Dominik",
""
],
[
"Schoelkopf",
"Bernhard",
""
]
] |
1408.3002 | JooYeol Yun | Jooyeol Yun, Jun won Seo, and Taeseon Yoon | The New Approach on Fuzzy Decision Trees | null | Jooyeol Yun, Jun won Seo, and Taeseon Yoon (2014) THE NEW APPROACH
ON FUZZY DECISION TREES International Journal of Fuzzy Logic Systems (IJFLS)
Vol.4, No.3, July 2014 | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Decision trees have been widely used in machine learning. However, due to
some reasons, data collecting in real world contains a fuzzy and uncertain
form. The decision tree should be able to handle such fuzzy data. This paper
presents a method to construct fuzzy decision tree. It proposes a fuzzy
decision tree induction method in iris flower data set, obtaining the entropy
from the distance between an average value and a particular value. It also
presents an experiment result that shows the accuracy compared to former ID3.
| [
{
"version": "v1",
"created": "Wed, 13 Aug 2014 13:23:58 GMT"
}
] | 1,407,974,400,000 | [
[
"Yun",
"Jooyeol",
""
],
[
"Seo",
"Jun won",
""
],
[
"Yoon",
"Taeseon",
""
]
] |
1408.5265 | Nikolaos Tziortziotis | Nikolaos Tziortziotis, Georgios Papagiannis and Konstantinos Blekas | A Bayesian Ensemble Regression Framework on the Angry Birds Game | Angry Birds AI Symposium, ECAI 2014 | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | An ensemble inference mechanism is proposed on the Angry Birds domain. It is
based on an efficient tree structure for encoding and representing game
screenshots, where it exploits its enhanced modeling capability. This has the
advantage to establish an informative feature space and modify the task of game
playing to a regression analysis problem. To this direction, we assume that
each type of object material and bird pair has its own Bayesian linear
regression model. In this way, a multi-model regression framework is designed
that simultaneously calculates the conditional expectations of several objects
and makes a target decision through an ensemble of regression models. Learning
procedure is performed according to an online estimation strategy for the model
parameters. We provide comparative experimental results on several game levels
that empirically illustrate the efficiency of the proposed methodology.
| [
{
"version": "v1",
"created": "Fri, 22 Aug 2014 11:15:25 GMT"
},
{
"version": "v2",
"created": "Mon, 25 Aug 2014 13:49:26 GMT"
}
] | 1,409,011,200,000 | [
[
"Tziortziotis",
"Nikolaos",
""
],
[
"Papagiannis",
"Georgios",
""
],
[
"Blekas",
"Konstantinos",
""
]
] |
1408.5377 | Thierry Petit | Alban Derrien, Thierry Petit and Stephane Zampelli | Dynamic Sweep Filtering Algorithm for FlexC | null | null | null | TR-Mines Nantes: 14/1/INFO | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We investigate cumulative scheduling in uncertain environments, using
constraint programming. We detail in this paper the dynamic sweep filtering
algorithm of the FlexC global constraint.
| [
{
"version": "v1",
"created": "Fri, 22 Aug 2014 18:45:57 GMT"
}
] | 1,408,924,800,000 | [
[
"Derrien",
"Alban",
""
],
[
"Petit",
"Thierry",
""
],
[
"Zampelli",
"Stephane",
""
]
] |
1408.5490 | Kieran Greer Dr | Kieran Greer | New Ideas for Brain Modelling 2 | This is an extended version of arXiv:1403.6274, with a different
conclusions section as well | K. Arai et al. (eds.), Intelligent Systems in Science and
Information 2014, Studies in Computational Intelligence, Vol. 591, pp. 23 -
39, Springer International Publishing Switzerland, 2015 | 10.1007/978-3-319-14654-6_2 | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | This paper describes a relatively simple way of allowing a brain model to
self-organise its concept patterns through nested structures. For a simulation,
time reduction is helpful and it would be able to show how patterns may form
and then fire in sequence, as part of a search or thought process. It uses a
very simple equation to show how the inhibitors in particular, can switch off
certain areas, to allow other areas to become the prominent ones and thereby
define the current brain state. This allows for a small amount of control over
what appears to be a chaotic structure inside of the brain. It is attractive
because it is still mostly mechanical and therefore can be added as an
automatic process, or the modelling of that. The paper also describes how the
nested pattern structure can be used as a basic counting mechanism. Another
mathematical conclusion provides a basis for maintaining memory or concept
patterns. The self-organisation can space itself through automatic processes.
This might allow new neurons to be added in a more even manner and could help
to maintain the concept integrity. The process might also help with finding
memory structures afterwards. This extended version integrates further with the
existing cognitive model and provides some new conclusions.
| [
{
"version": "v1",
"created": "Sat, 23 Aug 2014 11:05:00 GMT"
},
{
"version": "v2",
"created": "Tue, 2 Sep 2014 19:45:56 GMT"
}
] | 1,426,550,400,000 | [
[
"Greer",
"Kieran",
""
]
] |
1408.5507 | Florentin Smarandache | Florentin Smarandache, Mumtaz Ali, Muhammad Shabir | Soft Neutrosophic Algebraic Structures and Their Generalization | 264 pages | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Study of soft sets was first proposed by Molodtsov in 1999 to deal with
uncertainty in a non-parametric manner. The researchers did not pay attention
to soft set theory at that time but now the soft set theory has been developed
in many areas of mathematics. Algebraic structures using soft set theory are
very rapidly developed. In this book we developed soft neutrosophic algebraic
structures by using soft sets and neutrosophic algebraic structures. In this
book we study soft neutrosophic groups, soft neutrosophic semigroups, soft
neutrosophic loops, soft neutrosophic LA-semigroups, and their generalizations
respectively.
| [
{
"version": "v1",
"created": "Sat, 23 Aug 2014 15:44:16 GMT"
}
] | 1,409,011,200,000 | [
[
"Smarandache",
"Florentin",
""
],
[
"Ali",
"Mumtaz",
""
],
[
"Shabir",
"Muhammad",
""
]
] |
1408.6127 | Emmanuel Boidot | Emmanuel Boidot, Aude Marzuoli, Eric Feron | A Complete framework for ambush avoidance in realistic environments | null | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Operating vehicles in adversarial environments between a recurring
origin-destination pair requires new planning techniques. A two players
zero-sum game is introduced. The goal of the first player is to minimize the
expected casualties undergone by a convoy. The goal of the second player is to
maximize this damage. The outcome of the game is obtained via a linear program
that solves the corresponding minmax optimization problem over this outcome.
Different environment models are defined in order to compute routing strategies
over unstructured environments. To compare these methods for increasingly
accurate representations of the environment, a grid-based model is chosen to
represent the environment and the existence of a sufficient network size is
highlighted. A global framework for the generation of realistic routing
strategies between any two points is described. This framework requires a good
assessment of the potential casualties at any location, therefore the most
important parameters are identified. Finally the framework is tested on real
world environments.
| [
{
"version": "v1",
"created": "Tue, 26 Aug 2014 14:33:53 GMT"
}
] | 1,409,097,600,000 | [
[
"Boidot",
"Emmanuel",
""
],
[
"Marzuoli",
"Aude",
""
],
[
"Feron",
"Eric",
""
]
] |
1408.6186 | Sujit Das | Sujit Das and Samarjit Kar | Consensus and Consistency Level Optimization of Fuzzy Preference
Relation: A Soft Computing Approach | null | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In group decision making (GDM) problems fuzzy preference relations (FPR) are
widely used for representing decision makers' opinions on the set of
alternatives. In order to avoid misleading solutions, the study of consistency
and consensus has become a very important aspect. This article presents a
simulated annealing (SA) based soft computing approach to optimize the
consistency/consensus level (CCL) of a complete fuzzy preference relation in
order to solve a GDM problem. Consistency level indicates as expert's
preference quality and consensus level measures the degree of agreement among
experts' opinions. This study also suggests the set of experts for the
necessary modifications in their prescribed preference structures without
intervention of any moderator.
| [
{
"version": "v1",
"created": "Tue, 26 Aug 2014 17:27:00 GMT"
}
] | 1,409,097,600,000 | [
[
"Das",
"Sujit",
""
],
[
"Kar",
"Samarjit",
""
]
] |
1408.6520 | Shirin Sohrabi | Shirin Sohrabi and Octavian Udrea and Anton V. Riabov | Knowledge Engineering for Planning-Based Hypothesis Generation | This paper appears in the Proceedings of the Automated Planning and
Scheduling (ICAPS) Workshop on Knowledge Engineering for Planning and
Scheduling (KEPS) | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this paper, we address the knowledge engineering problems for hypothesis
generation motivated by applications that require timely exploration of
hypotheses under unreliable observations. We looked at two applications:
malware detection and intensive care delivery. In intensive care, the goal is
to generate plausible hypotheses about the condition of the patient from
clinical observations and further refine these hypotheses to create a recovery
plan for the patient. Similarly, preventing malware spread within a corporate
network involves generating hypotheses from network traffic data and selecting
preventive actions. To this end, building on the already established
characterization and use of AI planning for similar problems, we propose use of
planning for the hypothesis generation problem. However, to deal with
uncertainty, incomplete model description and unreliable observations, we need
to use a planner capable of generating multiple high-quality plans. To capture
the model description we propose a language called LTS++ and a web-based tool
that enables the specification of the LTS++ model and a set of observations. We
also proposed a 9-step process that helps provide guidance to the domain expert
in specifying the LTS++ model. The hypotheses are then generated by running a
planner on the translated LTS++ model and the provided trace. The hypotheses
can be visualized and shown to the analyst or can be further investigated
automatically.
| [
{
"version": "v1",
"created": "Wed, 27 Aug 2014 15:14:11 GMT"
}
] | 1,409,270,400,000 | [
[
"Sohrabi",
"Shirin",
""
],
[
"Udrea",
"Octavian",
""
],
[
"Riabov",
"Anton V.",
""
]
] |
1408.6706 | Odinaldo Rodrigues | D. Gabbay and O. Rodrigues | Equilibrium States in Numerical Argumentation Networks | null | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Given an argumentation network with initial values to the arguments, we look
for algorithms which can yield extensions compatible with such initial values.
We find that the best way of tackling this problem is to offer an iteration
formula that takes the initial values and the attack relation and iterates a
sequence of intermediate values that eventually converges leading to an
extension. The properties surrounding the application of the iteration formula
and its connection with other numerical and non-numerical techniques proposed
by others are thoroughly investigated in this paper.
| [
{
"version": "v1",
"created": "Thu, 28 Aug 2014 12:56:17 GMT"
},
{
"version": "v2",
"created": "Wed, 18 Mar 2015 18:09:21 GMT"
}
] | 1,426,723,200,000 | [
[
"Gabbay",
"D.",
""
],
[
"Rodrigues",
"O.",
""
]
] |
1408.6908 | Jose Hernandez-Orallo | Jose Hernandez-Orallo | AI Evaluation: past, present and future | 34 pages. This paper is largely superseded by the following paper:
"Evaluation in artificial intelligence: from task-oriented to
ability-oriented measurement" Journal of Artificial Intelligence Review
(2016). doi:10.1007/s10462-016-9505-7,
\url{http://dx.doi.org/10.1007/s10462-016-9505-7}. Please check and refer to
the journal paper | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Artificial intelligence develops techniques and systems whose performance
must be evaluated on a regular basis in order to certify and foster progress in
the discipline. We will describe and critically assess the different ways AI
systems are evaluated. We first focus on the traditional task-oriented
evaluation approach. We see that black-box (behavioural evaluation) is becoming
more and more common, as AI systems are becoming more complex and
unpredictable. We identify three kinds of evaluation: Human discrimination,
problem benchmarks and peer confrontation. We describe the limitations of the
many evaluation settings and competitions in these three categories and propose
several ideas for a more systematic and robust evaluation. We then focus on a
less customary (and challenging) ability-oriented evaluation approach, where a
system is characterised by its (cognitive) abilities, rather than by the tasks
it is designed to solve. We discuss several possibilities: the adaptation of
cognitive tests used for humans and animals, the development of tests derived
from algorithmic information theory or more general approaches under the
perspective of universal psychometrics.
| [
{
"version": "v1",
"created": "Fri, 29 Aug 2014 02:44:28 GMT"
},
{
"version": "v2",
"created": "Fri, 10 Oct 2014 02:16:32 GMT"
},
{
"version": "v3",
"created": "Sun, 21 Aug 2016 22:44:31 GMT"
}
] | 1,471,910,400,000 | [
[
"Hernandez-Orallo",
"Jose",
""
]
] |
1409.0069 | Amir Zidi | Amir Zidi and Amna Bouhana and Afef Fekih and Mourad Abed | Personalization of Itineraries search using Ontology and Rules to Avoid
Congestion in Urban Areas | null | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | There is a relatively small amount of research covering urban freight
movements. Most research dealing with the subject of urban mobility focuses on
passenger vehicles, not commercial vehicles hauling freight. However, in many
ways, urban freight transport contributes to congestion, air pollution, noise,
accident and more fuel consumption which raises logistic costs, and hence the
price of products. The main focus of this paper is to propose a new solution
for congestion in order to improve the distribution process of goods in urban
areas and optimize transportation cost, time of delivery, fuel consumption, and
environmental impact, while guaranteeing the safety of goods and passengers. A
novel technique for personalization in itinerary search based on city logistics
ontology and rules is proposed to overcome this problem. The integration of
personalization plays a key role in capturing or inferring the needs of each
stakeholder (user), and then satisfying these needs in a given context. The
proposed approach is implemented to an itinerary search problem for freight
transportation in urban areas to demonstrate its ability in facilitating
intelligent decision support by retrieving the best itinerary that satisfies
the most users preferences (stakeholders).
| [
{
"version": "v1",
"created": "Sat, 30 Aug 2014 00:24:27 GMT"
}
] | 1,409,616,000,000 | [
[
"Zidi",
"Amir",
""
],
[
"Bouhana",
"Amna",
""
],
[
"Fekih",
"Afef",
""
],
[
"Abed",
"Mourad",
""
]
] |
1409.0703 | Alejandro Sanchez Guinea | Alejandro Sanchez Guinea | On computable abstractions (a conceptual introduction) | 17 pages; clearer and more precise motivation; clearer concepts
presented; review on related works added | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | This paper introduces abstractions that are meaningful for computers and that
can be built and used according to computers' own criteria, i.e., computable
abstractions. It is analyzed how abstractions can be seen to serve as the
building blocks for the creation of one own's understanding of things, which is
essential in performing intellectual tasks. Thus, abstractional machines are
defined, which following a mechanical process can, based on computable
abstractions, build and use their own understanding of things. Abstractional
machines are illustrated through an example that outlines their application to
the task of natural language processing.
| [
{
"version": "v1",
"created": "Fri, 29 Aug 2014 18:29:53 GMT"
},
{
"version": "v2",
"created": "Tue, 9 Dec 2014 14:50:58 GMT"
},
{
"version": "v3",
"created": "Thu, 22 Jan 2015 13:21:52 GMT"
},
{
"version": "v4",
"created": "Sun, 29 Mar 2015 14:27:16 GMT"
}
] | 1,427,760,000,000 | [
[
"Guinea",
"Alejandro Sanchez",
""
]
] |
1409.1045 | Uwe Aickelin | Josie C. McCullochy, Chris J. Hinde, Christian Wagner and Uwe Aickelin | A Fuzzy Directional Distance Measure | Proceedings of the 2014 World Congress on Computational Intelligence
(WCCI 2014), pp. 141-148, 2014 | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The measure of distance between two fuzzy sets is a fundamental tool within
fuzzy set theory, however, distance measures currently within the literature
use a crisp value to represent the distance between fuzzy sets. A real valued
distance measure is developed into a fuzzy distance measure which better
reflects the uncertainty inherent in fuzzy sets and a fuzzy directional
distance measure is presented, which accounts for the direction of change
between fuzzy sets. A multiplicative version is explored as a full maximal
assignment is computationally intractable so an intermediate solution is
offered.
| [
{
"version": "v1",
"created": "Wed, 3 Sep 2014 11:48:23 GMT"
}
] | 1,409,788,800,000 | [
[
"McCullochy",
"Josie C.",
""
],
[
"Hinde",
"Chris J.",
""
],
[
"Wagner",
"Christian",
""
],
[
"Aickelin",
"Uwe",
""
]
] |
1409.1046 | Uwe Aickelin | Josie McCulloch, Christian Wagner and Uwe Aickelin | Analysing Fuzzy Sets Through Combining Measures of Similarity and
Distance | Proceedings of the 2014 World Congress on Computational Intelligence
(WCCI 2014), pp. 155-162, 2014 | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Reasoning with fuzzy sets can be achieved through measures such as similarity
and distance. However, these measures can often give misleading results when
considered independently, for example giving the same value for two different
pairs of fuzzy sets. This is particularly a problem where many fuzzy sets are
generated from real data, and while two different measures may be used to
automatically compare such fuzzy sets, it is difficult to interpret two
different results. This is especially true where a large number of fuzzy sets
are being compared as part of a reasoning system. This paper introduces a
method for combining the results of multiple measures into a single measure for
the purpose of analysing and comparing fuzzy sets. The combined measure
alleviates ambiguous results and aids in the automatic comparison of fuzzy
sets. The properties of the combined measure are given, and demonstrations are
presented with discussions on the advantages over using a single measure.
| [
{
"version": "v1",
"created": "Wed, 3 Sep 2014 11:52:07 GMT"
}
] | 1,409,788,800,000 | [
[
"McCulloch",
"Josie",
""
],
[
"Wagner",
"Christian",
""
],
[
"Aickelin",
"Uwe",
""
]
] |
1409.1170 | Kamran Latif | Kamran Latif | Hybrid Systems Knowledge Representation Using Modelling Environment
System Techniques Artificial Intelligence | null | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Knowledge-based or Artificial Intelligence techniques are used increasingly
as alternatives to more classical techniques to model ENVIRONMENTAL SYSTEMS.
Use of Artificial Intelligence (AI) in environmental modelling has increased
with recognition of its potential. In this paper we examine the DIFFERENT
TECHNIQUES of Artificial intelligence with profound examples of human
perception, learning and reasoning to solve complex problems. However with the
increase of complexity better methods are required. Keeping in view of the
above some researchers introduced the idea of hybrid mechanism in which two or
more methods can be combined which seems to be a positive effort for creating a
more complex; advanced and intelligent system which has the capability to in-
cooperate human decisions thus driving the landscape changes.
| [
{
"version": "v1",
"created": "Wed, 3 Sep 2014 17:04:58 GMT"
},
{
"version": "v2",
"created": "Sat, 13 Sep 2014 18:23:11 GMT"
}
] | 1,410,825,600,000 | [
[
"Latif",
"Kamran",
""
]
] |
1409.1686 | Fr\'ed\'eric Saubion | Adrien Go\"effon and Fr\'ed\'eric Lardeux and Fr\'ed\'eric Saubion | Simulating Non Stationary Operators in Search Algorithms | null | null | 10.1016/j.asoc.2015.09.024 | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this paper, we propose a model for simulating search operators whose
behaviour often changes continuously during the search. In these scenarios, the
performance of the operators decreases when they are applied. This is motivated
by the fact that operators for optimization problems are often roughly
classified into exploitation operators and exploration operators. Our
simulation model is used to compare the different performances of operator
selection policies and clearly identify their ability to adapt to such specific
operators behaviours. The experimental study provides interesting results on
the respective behaviours of operator selection policies when faced to such non
stationary search scenarios.
| [
{
"version": "v1",
"created": "Fri, 5 Sep 2014 08:29:35 GMT"
}
] | 1,552,262,400,000 | [
[
"Goëffon",
"Adrien",
""
],
[
"Lardeux",
"Frédéric",
""
],
[
"Saubion",
"Frédéric",
""
]
] |
1409.3653 | Lihong Li | Lihong Li and Remi Munos and Csaba Szepesvari | On Minimax Optimal Offline Policy Evaluation | null | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | This paper studies the off-policy evaluation problem, where one aims to
estimate the value of a target policy based on a sample of observations
collected by another policy. We first consider the multi-armed bandit case,
establish a minimax risk lower bound, and analyze the risk of two standard
estimators. It is shown, and verified in simulation, that one is minimax
optimal up to a constant, while another can be arbitrarily worse, despite its
empirical success and popularity. The results are applied to related problems
in contextual bandits and fixed-horizon Markov decision processes, and are also
related to semi-supervised learning.
| [
{
"version": "v1",
"created": "Fri, 12 Sep 2014 06:10:15 GMT"
}
] | 1,410,739,200,000 | [
[
"Li",
"Lihong",
""
],
[
"Munos",
"Remi",
""
],
[
"Szepesvari",
"Csaba",
""
]
] |
1409.4164 | Tomas Trescak | Tomas Trescak, Carles Sierra, Simeon Simoff, Ramon Lopez de Mantaras | Dispute Resolution Using Argumentation-Based Mediation | 6 pages | null | null | null | cs.AI | http://creativecommons.org/licenses/by/3.0/ | Mediation is a process, in which both parties agree to resolve their dispute
by negotiating over alternative solutions presented by a mediator. In order to
construct such solutions, mediation brings more information and knowledge, and,
if possible, resources to the negotiation table. The contribution of this paper
is the automated mediation machinery which does that. It presents an
argumentation-based mediation approach that extends the logic-based approach to
argumentation-based negotiation involving BDI agents. The paper describes the
mediation algorithm. For comparison it illustrates the method with a case study
used in an earlier work. It demonstrates how the computational mediator can
deal with realistic situations in which the negotiating agents would otherwise
fail due to lack of knowledge and/or resources.
| [
{
"version": "v1",
"created": "Mon, 15 Sep 2014 07:14:37 GMT"
}
] | 1,410,825,600,000 | [
[
"Trescak",
"Tomas",
""
],
[
"Sierra",
"Carles",
""
],
[
"Simoff",
"Simeon",
""
],
[
"de Mantaras",
"Ramon Lopez",
""
]
] |
1409.5223 | Ben Ruijl | Ben Ruijl, Aske Plaat, Jos Vermaseren, Jaap van den Herik | Why Local Search Excels in Expression Simplification | null | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Simplifying expressions is important to make numerical integration of large
expressions from High Energy Physics tractable. To this end, Horner's method
can be used. Finding suitable Horner schemes is assumed to be hard, due to the
lack of local heuristics. Recently, MCTS was reported to be able to find near
optimal schemes. However, several parameters had to be fine-tuned manually. In
this work, we investigate the state space properties of Horner schemes and find
that the domain is relatively flat and contains only a few local minima. As a
result, the Horner space is appropriate to be explored by Stochastic Local
Search (SLS), which has only two parameters: the number of iterations
(computation time) and the neighborhood structure. We found a suitable
neighborhood structure, leaving only the allowed computation time as a
parameter. We performed a range of experiments. The results obtained by SLS are
similar or better than those obtained by MCTS. Furthermore, we show that SLS
obtains the good results at least 10 times faster. Using SLS, we can speed up
numerical integration of many real-world large expressions by at least a factor
of 24. For High Energy Physics this means that numerical integrations that took
weeks can now be done in hours.
| [
{
"version": "v1",
"created": "Thu, 18 Sep 2014 08:21:25 GMT"
}
] | 1,411,084,800,000 | [
[
"Ruijl",
"Ben",
""
],
[
"Plaat",
"Aske",
""
],
[
"Vermaseren",
"Jos",
""
],
[
"Herik",
"Jaap van den",
""
]
] |
1409.5317 | Scott MacLean | Scott MacLean and George Labahn | A Bayesian model for recognizing handwritten mathematical expressions | null | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Recognizing handwritten mathematics is a challenging classification problem,
requiring simultaneous identification of all the symbols comprising an input as
well as the complex two-dimensional relationships between symbols and
subexpressions. Because of the ambiguity present in handwritten input, it is
often unrealistic to hope for consistently perfect recognition accuracy. We
present a system which captures all recognizable interpretations of the input
and organizes them in a parse forest from which individual parse trees may be
extracted and reported. If the top-ranked interpretation is incorrect, the user
may request alternates and select the recognition result they desire. The tree
extraction step uses a novel probabilistic tree scoring strategy in which a
Bayesian network is constructed based on the structure of the input, and each
joint variable assignment corresponds to a different parse tree. Parse trees
are then reported in order of decreasing probability. Two accuracy evaluations
demonstrate that the resulting recognition system is more accurate than
previous versions (which used non-probabilistic methods) and other academic
math recognizers.
| [
{
"version": "v1",
"created": "Thu, 18 Sep 2014 14:45:24 GMT"
}
] | 1,411,084,800,000 | [
[
"MacLean",
"Scott",
""
],
[
"Labahn",
"George",
""
]
] |
1409.5340 | Paolo Liberatore | Paolo Liberatore | Belief revision by examples | null | null | 10.1145/2818645 | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | A common assumption in belief revision is that the reliability of the
information sources is either given, derived from temporal information, or the
same for all. This article does not describe a new semantics for integration
but the problem of obtaining the reliability of the sources given the result of
a previous merging. As an example, the relative reliability of two sensors can
be assessed given some certain observation, and allows for subsequent mergings
of data coming from them.
| [
{
"version": "v1",
"created": "Thu, 18 Sep 2014 15:31:03 GMT"
}
] | 1,617,926,400,000 | [
[
"Liberatore",
"Paolo",
""
]
] |
1409.5719 | Sebastien Verel | Manuel L\'opez-Ib\'a\~nez (IRIDIA), Arnaud Liefooghe (INRIA Lille -
Nord Europe, LIFL), S\'ebastien Verel (LISIC) | Local Optimal Sets and Bounded Archiving on Multi-objective
NK-Landscapes with Correlated Objectives | appears in Parallel Problem Solving from Nature - PPSN XIII,
Ljubljana : Slovenia (2014) | null | 10.1007/978-3-319-10762-2_61 | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The properties of local optimal solutions in multi-objective combinatorial
optimization problems are crucial for the effectiveness of local search
algorithms, particularly when these algorithms are based on Pareto dominance.
Such local search algorithms typically return a set of mutually nondominated
Pareto local optimal (PLO) solutions, that is, a PLO-set. This paper
investigates two aspects of PLO-sets by means of experiments with Pareto local
search (PLS). First, we examine the impact of several problem characteristics
on the properties of PLO-sets for multi-objective NK-landscapes with correlated
objectives. In particular, we report that either increasing the number of
objectives or decreasing the correlation between objectives leads to an
exponential increment on the size of PLO-sets, whereas the variable correlation
has only a minor effect. Second, we study the running time and the quality
reached when using bounding archiving methods to limit the size of the archive
handled by PLS, and thus, the maximum size of the PLO-set found. We argue that
there is a clear relationship between the running time of PLS and the
difficulty of a problem instance.
| [
{
"version": "v1",
"created": "Fri, 19 Sep 2014 16:44:40 GMT"
}
] | 1,411,344,000,000 | [
[
"López-Ibáñez",
"Manuel",
"",
"IRIDIA"
],
[
"Liefooghe",
"Arnaud",
"",
"INRIA Lille -\n Nord Europe, LIFL"
],
[
"Verel",
"Sébastien",
"",
"LISIC"
]
] |
1409.5752 | Sebastien Verel | Bilel Derbel (INRIA Lille - Nord Europe, LIFL), Dimo Brockhoff (INRIA
Lille - Nord Europe), Arnaud Liefooghe (INRIA Lille - Nord Europe, LIFL),
S\'ebastien Verel (LISIC) | On the Impact of Multiobjective Scalarizing Functions | appears in Parallel Problem Solving from Nature - PPSN XIII,
Ljubljana : Slovenia (2014) | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Recently, there has been a renewed interest in decomposition-based approaches
for evolutionary multiobjective optimization. However, the impact of the choice
of the underlying scalarizing function(s) is still far from being well
understood. In this paper, we investigate the behavior of different scalarizing
functions and their parameters. We thereby abstract firstly from any specific
algorithm and only consider the difficulty of the single scalarized problems in
terms of the search ability of a (1+lambda)-EA on biobjective NK-landscapes.
Secondly, combining the outcomes of independent single-objective runs allows
for more general statements on set-based performance measures. Finally, we
investigate the correlation between the opening angle of the scalarizing
function's underlying contour lines and the position of the final solution in
the objective space. Our analysis is of fundamental nature and sheds more light
on the key characteristics of multiobjective scalarizing functions.
| [
{
"version": "v1",
"created": "Fri, 19 Sep 2014 18:41:36 GMT"
}
] | 1,411,344,000,000 | [
[
"Derbel",
"Bilel",
"",
"INRIA Lille - Nord Europe, LIFL"
],
[
"Brockhoff",
"Dimo",
"",
"INRIA\n Lille - Nord Europe"
],
[
"Liefooghe",
"Arnaud",
"",
"INRIA Lille - Nord Europe, LIFL"
],
[
"Verel",
"Sébastien",
"",
"LISIC"
]
] |
1409.6287 | Ji\v{r}\'i Vomlel | Ji\v{r}\'i Vomlel and Petr Tichavsk\'y | On tensor rank of conditional probability tables in Bayesian networks | null | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | A difficult task in modeling with Bayesian networks is the elicitation of
numerical parameters of Bayesian networks. A large number of parameters is
needed to specify a conditional probability table (CPT) that has a larger
parent set. In this paper we show that, most CPTs from real applications of
Bayesian networks can actually be very well approximated by tables that require
substantially less parameters. This observation has practical consequence not
only for model elicitation but also for efficient probabilistic reasoning with
these networks.
| [
{
"version": "v1",
"created": "Mon, 22 Sep 2014 19:32:15 GMT"
}
] | 1,470,787,200,000 | [
[
"Vomlel",
"Jiří",
""
],
[
"Tichavský",
"Petr",
""
]
] |
1409.7186 | Andrea Schaerf | Ruggero Bellio, Sara Ceschia, Luca Di Gaspero, Andrea Schaerf, Tommaso
Urli | Feature-based tuning of simulated annealing applied to the
curriculum-based course timetabling problem | null | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We consider the university course timetabling problem, which is one of the
most studied problems in educational timetabling. In particular, we focus our
attention on the formulation known as the curriculum-based course timetabling
problem, which has been tackled by many researchers and for which there are
many available benchmarks.
The contribution of this paper is twofold. First, we propose an effective and
robust single-stage simulated annealing method for solving the problem.
Secondly, we design and apply an extensive and statistically-principled
methodology for the parameter tuning procedure. The outcome of this analysis is
a methodology for modeling the relationship between search method parameters
and instance features that allows us to set the parameters for unseen instances
on the basis of a simple inspection of the instance itself. Using this
methodology, our algorithm, despite its apparent simplicity, has been able to
achieve high quality results on a set of popular benchmarks.
A final contribution of the paper is a novel set of real-world instances,
which could be used as a benchmark for future comparison.
| [
{
"version": "v1",
"created": "Thu, 25 Sep 2014 08:53:04 GMT"
},
{
"version": "v2",
"created": "Wed, 8 Jul 2015 07:53:36 GMT"
}
] | 1,436,400,000,000 | [
[
"Bellio",
"Ruggero",
""
],
[
"Ceschia",
"Sara",
""
],
[
"Di Gaspero",
"Luca",
""
],
[
"Schaerf",
"Andrea",
""
],
[
"Urli",
"Tommaso",
""
]
] |
1409.8027 | J. G. Wolff | J. Gerard Wolff | Autonomous robots and the SP theory of intelligence | null | IEEE Access, 2, 1629-1651, 2014 | 10.1109/ACCESS.2014.2382753 | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | This article is about how the "SP theory of intelligence" and its realisation
in the "SP machine" (both outlined in the article) may help to solve
computer-related problems in the design of autonomous robots, meaning robots
that do not depend on external intelligence or power supplies, are mobile, and
are designed to exhibit as much human-like intelligence as possible. The
article is about: how to increase the computational and energy efficiency of
computers and reduce their bulk; how to achieve human-like versatility in
intelligence; and likewise for human-like adaptability in intelligence. The SP
system has potential for substantial gains in computational and energy
efficiency and reductions in the bulkiness of computers: by reducing the size
of data to be processed; by exploiting statistical information that the system
gathers; and via an updated version of Donald Hebb's concept of a "cell
assembly". Towards human-like versatility in intelligence, the SP system has
strengths in unsupervised learning, natural language processing, pattern
recognition, information retrieval, several kinds of reasoning, planning,
problem solving, and more, with seamless integration amongst structures and
functions. The SP system's strengths in unsupervised learning and other aspects
of intelligence may help to achieve human-like adaptability in intelligence
via: the learning of natural language; learning to see; building 3D models of
objects and of a robot's surroundings; learning regularities in the workings of
a robot and in the robot's environment; exploration and play; learning major
skills; and secondary forms of learning. Also discussed are: how the SP system
may process parallel streams of information; generalisation of knowledge,
correction of over-generalisations, and learning from dirty data; how to cut
the cost of learning; and reinforcements, motivations, goals, and
demonstration.
| [
{
"version": "v1",
"created": "Mon, 29 Sep 2014 08:41:01 GMT"
},
{
"version": "v2",
"created": "Fri, 23 Jan 2015 08:47:02 GMT"
}
] | 1,422,230,400,000 | [
[
"Wolff",
"J. Gerard",
""
]
] |
1409.8053 | J. G. Wolff | J. Gerard Wolff | Medical diagnosis as pattern recognition in a framework of information
compression by multiple alignment, unification and search | null | Decision Support Systems 42, 608-625, 2006 | 10.1016/j.dss.2005.02.005 | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | This paper describes a novel approach to medical diagnosis based on the SP
theory of computing and cognition. The main attractions of this approach are: a
format for representing diseases that is simple and intuitive; an ability to
cope with errors and uncertainties in diagnostic information; the simplicity of
storing statistical information as frequencies of occurrence of diseases; a
method for evaluating alternative diagnostic hypotheses that yields true
probabilities; and a framework that should facilitate unsupervised learning of
medical knowledge and the integration of medical diagnosis with other AI
applications.
| [
{
"version": "v1",
"created": "Mon, 29 Sep 2014 10:11:31 GMT"
}
] | 1,412,035,200,000 | [
[
"Wolff",
"J. Gerard",
""
]
] |
1409.8470 | Catarina Moreira | Catarina Moreira and Andreas Wichert | Interference Effects in Quantum Belief Networks | null | Applied Soft Computing, Volume 25, December 2014, Pages 64 - 85 | 10.1016/j.asoc.2014.09.008 | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Probabilistic graphical models such as Bayesian Networks are one of the most
powerful structures known by the Computer Science community for deriving
probabilistic inferences. However, modern cognitive psychology has revealed
that human decisions could not follow the rules of classical probability
theory, because humans cannot process large amounts of data in order to make
judgements. Consequently, the inferences performed are based on limited data
coupled with several heuristics, leading to violations of the law of total
probability. This means that probabilistic graphical models based on classical
probability theory are too limited to fully simulate and explain various
aspects of human decision making.
Quantum probability theory was developed in order to accommodate the
paradoxical findings that the classical theory could not explain. Recent
findings in cognitive psychology revealed that quantum probability can fully
describe human decisions in an elegant framework. Their findings suggest that,
before taking a decision, human thoughts are seen as superposed waves that can
interfere with each other, influencing the final decision.
In this work, we propose a new Bayesian Network based on the psychological
findings of cognitive scientists. We made experiments with two very well known
Bayesian Networks from the literature. The results obtained revealed that the
quantum like Bayesian Network can affect drastically the probabilistic
inferences, specially when the levels of uncertainty of the network are very
high (no pieces of evidence observed). When the levels of uncertainty are very
low, then the proposed quantum like network collapses to its classical
counterpart.
| [
{
"version": "v1",
"created": "Tue, 30 Sep 2014 10:43:30 GMT"
}
] | 1,412,121,600,000 | [
[
"Moreira",
"Catarina",
""
],
[
"Wichert",
"Andreas",
""
]
] |
1410.0281 | Tom De Smedt | Tom De Smedt | Modeling Creativity: Case Studies in Python | p. 165, University Press Antwerp, ISBN 978-90-5718-260-0 | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Modeling Creativity (doctoral dissertation, 2013) explores how creativity can
be represented using computational approaches. Our aim is to construct computer
models that exhibit creativity in an artistic context, that is, that are
capable of generating or evaluating an artwork (visual or linguistic), an
interesting new idea, a subjective opinion. The research was conducted in
2008-2012 at the Computational Linguistics Research Group (CLiPS, University of
Antwerp) under the supervision of Prof. Walter Daelemans. Prior research was
also conducted at the Experimental Media Research Group (EMRG, St. Lucas
University College of Art & Design Antwerp) under the supervision of Lucas
Nijs.
Modeling Creativity examines creativity in a number of different
perspectives: from its origins in nature, which is essentially blind, to humans
and machines, and from generating creative ideas to evaluating and learning
their novelty and usefulness. We will use a hands-on approach with case studies
and examples in the Python programming language.
| [
{
"version": "v1",
"created": "Sun, 10 Aug 2014 20:54:39 GMT"
}
] | 1,412,208,000,000 | [
[
"De Smedt",
"Tom",
""
]
] |
1410.0369 | Roman Yampolskiy | Roman V. Yampolskiy | The Universe of Minds | null | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The paper attempts to describe the space of possible mind designs by first
equating all minds to software. Next it proves some interesting properties of
the mind design space such as infinitude of minds, size and representation
complexity of minds. A survey of mind design taxonomies is followed by a
proposal for a new field of investigation devoted to study of minds,
intellectology, a list of open problems for this new field is presented.
| [
{
"version": "v1",
"created": "Wed, 1 Oct 2014 20:02:05 GMT"
}
] | 1,412,294,400,000 | [
[
"Yampolskiy",
"Roman V.",
""
]
] |
1410.1776 | Maurizio Proietti | Fabrizio Smith, Maurizio Proietti | Ontology-based Representation and Reasoning on Process Models: A Logic
Programming Approach | null | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We propose a framework grounded in Logic Programming for representing and
reasoning about business processes from both the procedural and ontological
point of views. In particular, our goal is threefold: (1) define a logical
language and a formal semantics for process models enriched with ontology-based
annotations; (2) provide an effective inference mechanism that supports the
combination of reasoning services dealing with the structural definition of a
process model, its behavior, and the domain knowledge related to the
participating business entities; (3) implement such a theoretical framework
into a process modeling and reasoning platform. To this end we define a process
ontology coping with a relevant fragment of the popular BPMN modeling notation.
The behavioral semantics of a process is defined as a state transition system
by following an approach similar to the Fluent Calculus, and allows us to
specify state change in terms of preconditions and effects of the enactment of
activities. Then we show how the procedural process knowledge can be seamlessly
integrated with the domain knowledge specified by using the OWL 2 RL rule-based
ontology language. Our framework provides a wide range of reasoning services,
including CTL model checking, which can be performed by using standard Logic
Programming inference engines through a goal-oriented, efficient, sound and
complete evaluation procedure. We also present a software environment
implementing the proposed framework, and we report on an experimental
evaluation of the system, whose results are encouraging and show the viability
of the approach.
| [
{
"version": "v1",
"created": "Tue, 7 Oct 2014 15:39:03 GMT"
}
] | 1,412,726,400,000 | [
[
"Smith",
"Fabrizio",
""
],
[
"Proietti",
"Maurizio",
""
]
] |
1410.2056 | Taymaz Rahkar Farshi | Taymaz Rahkar-Farshi, Sara Behjat-Jamal, Mohammad-Reza Feizi-Derakhshi | An improved multimodal PSO method based on electrostatic interaction
using n- nearest-neighbor local search | 10 pages, 8 figures, International Journal of Artificial Intelligence
& Applications (IJAIA), Vol. 5, No. 5, September 2014 | null | 10.5121/ijaia.2014.5506 | null | cs.AI | http://creativecommons.org/licenses/publicdomain/ | In this paper, an improved multimodal optimization (MMO) algorithm,called
LSEPSO,has been proposed. LSEPSO combined Electrostatic Particle Swarm
Optimization (EPSO) algorithm and a local search method and then made some
modification on them. It has been shown to improve global and local optima
finding ability of the algorithm. This algorithm useda modified local search to
improve particle's personal best, which used n-nearest-neighbour instead of
nearest-neighbour. Then, by creating n new points among each particle and n
nearest particles, it tried to find a point which could be the alternative of
particle's personal best. This method prevented particle's attenuation and
following a specific particle by its neighbours. The performed tests on a
number of benchmark functions clearly demonstrated that the improved algorithm
is able to solve MMO problems and outperform other tested algorithms in this
article.
| [
{
"version": "v1",
"created": "Wed, 8 Oct 2014 10:48:03 GMT"
}
] | 1,412,812,800,000 | [
[
"Rahkar-Farshi",
"Taymaz",
""
],
[
"Behjat-Jamal",
"Sara",
""
],
[
"Feizi-Derakhshi",
"Mohammad-Reza",
""
]
] |
1410.2063 | Stefania Costantini | Stefania Costantini | Committment-Based Data-Aware Multi-Agent-Contexts Systems | Draft of a paper submitted to an International Conference | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Communication and interaction among agents have been the subject of extensive
investigation since many years. Commitment-based communication, where
communicating agents are seen as a debtor agent who is committed to a creditor
agent to bring about something (possibly under some conditions) is now very
well-established. The approach of DACMAS (Data-Aware Commitment-based MAS)
lifts commitment-related approaches proposed in the literature from a
propositional to a first-order setting via the adoption the DRL-Lite
Description Logic. Notably, DACMASs provide, beyond commitments, simple forms
of inter-agent event-based communication. Yet, the aspect is missing of making
a MAS able to acquire knowledge from contexts which are not agents and which
are external to the MAS. This topic is coped with in Managed MCSs (Managed
Multi-Context Systems), where however exchanges are among knowledge bases and
not agents. In this paper, we propose the new approach of DACmMCMASs
(Data-Aware Commitment-based managed Multi- Context MAS), so as to obtain a
commitment-based first-order agent system which is able to interact with
heterogeneous external information sources. We show that DACmMCMASs retain the
nice formal properties of the original approaches.
| [
{
"version": "v1",
"created": "Wed, 8 Oct 2014 11:11:13 GMT"
}
] | 1,412,812,800,000 | [
[
"Costantini",
"Stefania",
""
]
] |
1410.2442 | Steven Schockaert | Steven Schockaert and Sanjiang Li | Realizing RCC8 networks using convex regions | null | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | RCC8 is a popular fragment of the region connection calculus, in which
qualitative spatial relations between regions, such as adjacency, overlap and
parthood, can be expressed. While RCC8 is essentially dimensionless, most
current applications are confined to reasoning about two-dimensional or
three-dimensional physical space. In this paper, however, we are mainly
interested in conceptual spaces, which typically are high-dimensional Euclidean
spaces in which the meaning of natural language concepts can be represented
using convex regions. The aim of this paper is to analyze how the restriction
to convex regions constrains the realizability of networks of RCC8 relations.
First, we identify all ways in which the set of RCC8 base relations can be
restricted to guarantee that consistent networks can be convexly realized in
respectively 1D, 2D, 3D, and 4D. Most surprisingly, we find that if the
relation 'partially overlaps' is disallowed, all consistent atomic RCC8
networks can be convexly realized in 4D. If instead refinements of the relation
'part of' are disallowed, all consistent atomic RCC8 relations can be convexly
realized in 3D. We furthermore show, among others, that any consistent RCC8
network with 2n+1 variables can be realized using convex regions in the
n-dimensional Euclidean space.
| [
{
"version": "v1",
"created": "Thu, 9 Oct 2014 12:54:08 GMT"
},
{
"version": "v2",
"created": "Fri, 17 Oct 2014 10:14:17 GMT"
}
] | 1,413,763,200,000 | [
[
"Schockaert",
"Steven",
""
],
[
"Li",
"Sanjiang",
""
]
] |
1410.4182 | Biju Issac | J. R. Modapothala, and B. Issac | Analysis of corporate environmental reports using statistical techniques
and data mining | 8 pages | Communications of the IBIMA, 10(6), 32-38. (2009) | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Measuring the effectiveness of corporate environmental reports, it being
highly qualitative and less regulated, is often considered as a daunting task.
The task becomes more complex if comparisons are to be performed. This study is
undertaken to overcome the physical verification problems by implementing data
mining technique. It further explores on the effectiveness by performing
exploratory analysis and structural equation model to bring out the significant
linkages between the selected 10 variables. Samples of five hundred and thirty
nine reports across various countries are used from an international directory
to perform the statistical analysis like: One way ANOVA (Analysis of Variance),
MDA (Multivariate Discriminant Analysis) and SEM (Structural Equation
Modeling). The results indicate the significant differences among the various
types of industries in their environmental reporting, and the exploratory
factors like stakeholder, organization strategy and industrial oriented
factors, proved significant. The major accomplishment is that the findings
correlate with the conceptual frame work of GRI.
| [
{
"version": "v1",
"created": "Wed, 8 Oct 2014 09:23:43 GMT"
}
] | 1,413,417,600,000 | [
[
"Modapothala",
"J. R.",
""
],
[
"Issac",
"B.",
""
]
] |
1410.5215 | Artem Revenko | Sergei O. Kuznetsov and Artem Revenko | Interactive Error Correction in Implicative Theories | null | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Errors in implicative theories coming from binary data are studied. First,
two classes of errors that may affect implicative theories are singled out. Two
approaches for finding errors of these classes are proposed, both of them based
on methods of Formal Concept Analysis. The first approach uses the cardinality
minimal (canonical or Duquenne-Guigues) implication base. The construction of
such a base is computationally intractable. Using an alternative approach one
checks possible errors on the fly in polynomial time via computing closures of
subsets of attributes. Both approaches are interactive, based on questions
about the validity of certain implications. Results of computer experiments are
presented and discussed.
| [
{
"version": "v1",
"created": "Mon, 20 Oct 2014 10:04:39 GMT"
}
] | 1,413,849,600,000 | [
[
"Kuznetsov",
"Sergei O.",
""
],
[
"Revenko",
"Artem",
""
]
] |
1410.5738 | Debdipta Goswami | Debdipta Goswami and Heiko Hamann | Investigation of A Collective Decision Making System of Different
Neighbourhood-Size Based on Hyper-Geometric Distribution | 9 pages, 20 figures | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The study of collective decision making system has become the central part of
the Swarm- Intelligence Related research in recent years. The most challenging
task of modelling a collec- tive decision making system is to develop the
macroscopic stochastic equation from its microscopic model. In this report we
have investigated the behaviour of a collective decision making system with
specified microscopic rules that resemble the chemical reaction and used
different group size. Then we ventured to derive a generalized analytical model
of a collective-decision system using hyper-geometric distribution.
Index Terms-swarm; collective decision making; noise; group size;
hyper-geometric distribution
| [
{
"version": "v1",
"created": "Tue, 21 Oct 2014 16:48:52 GMT"
}
] | 1,413,936,000,000 | [
[
"Goswami",
"Debdipta",
""
],
[
"Hamann",
"Heiko",
""
]
] |
1410.5859 | Ramanathan Guha | Ramanathan Guha | Towards a Model Theory for Distributed Representations | null | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Distributed representations (such as those based on embeddings) and discrete
representations (such as those based on logic) have complementary strengths. We
explore one possible approach to combining these two kinds of representations.
We present a model theory/semantics for first order logic based on vectors of
reals. We describe the model theory, discuss some interesting properties of
such a system and present a simple approach to query answering.
| [
{
"version": "v1",
"created": "Tue, 21 Oct 2014 21:15:45 GMT"
},
{
"version": "v2",
"created": "Thu, 30 Oct 2014 13:43:31 GMT"
},
{
"version": "v3",
"created": "Thu, 5 Feb 2015 03:06:09 GMT"
}
] | 1,423,180,800,000 | [
[
"Guha",
"Ramanathan",
""
]
] |
1410.6142 | Mark Riedl | Mark O. Riedl | The Lovelace 2.0 Test of Artificial Creativity and Intelligence | 2 pages | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Observing that the creation of certain types of artistic artifacts
necessitate intelligence, we present the Lovelace 2.0 Test of creativity as an
alternative to the Turing Test as a means of determining whether an agent is
intelligent. The Lovelace 2.0 Test builds off prior tests of creativity and
additionally provides a means of directly comparing the relative intelligence
of different agents.
| [
{
"version": "v1",
"created": "Wed, 22 Oct 2014 18:59:31 GMT"
},
{
"version": "v2",
"created": "Thu, 23 Oct 2014 15:09:53 GMT"
},
{
"version": "v3",
"created": "Mon, 22 Dec 2014 03:24:06 GMT"
}
] | 1,419,292,800,000 | [
[
"Riedl",
"Mark O.",
""
]
] |
1410.6519 | David Tolpin | David Tolpin | Justifying and Improving Meta-Agent Conflict-Based Search | 7 pages | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The Meta-Agent Conflict-Based Search~(MA-CBS) is a recently proposed
algorithm for the multi-agent path finding problem. The algorithm is an
extension of Conflict-Based Search~(CBS), which automatically merges
conflicting agents into meta-agents if the number of conflicts exceeds a
certain threshold. However, the decision to merge agents is made according to
an empirically chosen fixed threshold on the number of conflicts. The best
threshold depends both on the domain and on the number of agents, and the
nature of the dependence is not clearly understood.
We suggest a justification for the use of a fixed threshold on the number of
conflicts based on the analysis of a model problem. Following the suggested
justification, we introduce new decision policies for the MA-CBS algorithm,
which considerably improve the algorithm's performance. The improved variants
of the algorithm are evaluated on several sets of problems, chosen to underline
different aspects of the algorithms.
| [
{
"version": "v1",
"created": "Thu, 23 Oct 2014 22:50:35 GMT"
}
] | 1,414,368,000,000 | [
[
"Tolpin",
"David",
""
]
] |
1410.6641 | Paul Swoboda | Paul Swoboda, Alexander Shekhovtsov, J\"org Hendrik Kappes, Christoph
Schn\"orr and Bogdan Savchynskyy | Partial Optimality by Pruning for MAP-Inference with General Graphical
Models | 16 pages, 4 tables and 4 figures | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We consider the energy minimization problem for undirected graphical models,
also known as MAP-inference problem for Markov random fields which is NP-hard
in general. We propose a novel polynomial time algorithm to obtain a part of
its optimal non-relaxed integral solution. Our algorithm is initialized with
variables taking integral values in the solution of a convex relaxation of the
MAP-inference problem and iteratively prunes those, which do not satisfy our
criterion for partial optimality. We show that our pruning strategy is in a
certain sense theoretically optimal. Also empirically our method outperforms
previous approaches in terms of the number of persistently labelled variables.
The method is very general, as it is applicable to models with arbitrary
factors of an arbitrary order and can employ any solver for the considered
relaxed problem. Our method's runtime is determined by the runtime of the
convex relaxation solver for the MAP-inference problem.
| [
{
"version": "v1",
"created": "Fri, 24 Oct 2014 10:32:18 GMT"
},
{
"version": "v2",
"created": "Tue, 18 Aug 2015 06:40:57 GMT"
}
] | 1,439,942,400,000 | [
[
"Swoboda",
"Paul",
""
],
[
"Shekhovtsov",
"Alexander",
""
],
[
"Kappes",
"Jörg Hendrik",
""
],
[
"Schnörr",
"Christoph",
""
],
[
"Savchynskyy",
"Bogdan",
""
]
] |
1410.6671 | Yong Lai | Yong Lai, Dayou Liu, Minghao Yin | Augmenting Ordered Binary Decision Diagrams with Conjunctive
Decomposition | 7 pages, 6 figures | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | This paper augments OBDD with conjunctive decomposition to propose a
generalization called OBDD[$\wedge$]. By imposing reducedness and the finest
$\wedge$-decomposition bounded by integer $i$
($\wedge_{\widehat{i}}$-decomposition) on OBDD[$\wedge$], we identify a family
of canonical languages called ROBDD[$\wedge_{\widehat{i}}$], where
ROBDD[$\wedge_{\widehat{0}}$] is equivalent to ROBDD. We show that the
succinctness of ROBDD[$\wedge_{\widehat{i}}$] is strictly increasing when $i$
increases. We introduce a new time-efficiency criterion called rapidity which
reflects that exponential operations may be preferable if the language can be
exponentially more succinct, and show that: the rapidity of each operation on
ROBDD[$\wedge_{\widehat{i}}$] is increasing when $i$ increases; particularly,
the rapidity of some operations (e.g., conjoining) is strictly increasing.
Finally, our empirical results show that: a) the size of
ROBDD[$\wedge_{\widehat{i}}$] is normally not larger than that of the
equivalent \ROBDDC{\widehat{i+1}}; b) conjoining two
ROBDD[$\wedge_{\widehat{1}}$]s is more efficient than conjoining two
ROBDD[$\wedge_{\widehat{0}}$]s in most cases, where the former is NP-hard but
the latter is in P; and c) the space-efficiency of
ROBDD[$\wedge_{\widehat{\infty}}$] is comparable with that of d-DNNF and that
of another canonical generalization of \ROBDD{} called SDD.
| [
{
"version": "v1",
"created": "Fri, 24 Oct 2014 13:07:53 GMT"
}
] | 1,414,368,000,000 | [
[
"Lai",
"Yong",
""
],
[
"Liu",
"Dayou",
""
],
[
"Yin",
"Minghao",
""
]
] |
1410.6690 | Emmanuel Lonca | Daniel Le Berre and Emmanuel Lonca and Pierre Marquis | On the Complexity of Optimization Problems based on Compiled NNF
Representations | null | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Optimization is a key task in a number of applications. When the set of
feasible solutions under consideration is of combinatorial nature and described
in an implicit way as a set of constraints, optimization is typically NP-hard.
Fortunately, in many problems, the set of feasible solutions does not often
change and is independent from the user's request. In such cases, compiling the
set of constraints describing the set of feasible solutions during an off-line
phase makes sense, if this compilation step renders computationally easier the
generation of a non-dominated, yet feasible solution matching the user's
requirements and preferences (which are only known at the on-line step). In
this article, we focus on propositional constraints. The subsets L of the NNF
language analyzed in Darwiche and Marquis' knowledge compilation map are
considered. A number of families F of representations of objective functions
over propositional variables, including linear pseudo-Boolean functions and
more sophisticated ones, are considered. For each language L and each family F,
the complexity of generating an optimal solution when the constraints are
compiled into L and optimality is to be considered w.r.t. a function from F is
identified.
| [
{
"version": "v1",
"created": "Fri, 24 Oct 2014 14:26:04 GMT"
}
] | 1,414,368,000,000 | [
[
"Berre",
"Daniel Le",
""
],
[
"Lonca",
"Emmanuel",
""
],
[
"Marquis",
"Pierre",
""
]
] |
1410.6960 | Vilem Vychodil | Vilem Vychodil | Parameterizing the semantics of fuzzy attribute implications by systems
of isotone Galois connections | null | IEEE Trans. Fuzzy Systems 24(3): 645-660 (2016) | 10.1109/TFUZZ.2015.2470530 | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We study the semantics of fuzzy if-then rules called fuzzy attribute
implications parameterized by systems of isotone Galois connections. The rules
express dependencies between fuzzy attributes in object-attribute incidence
data. The proposed parameterizations are general and include as special cases
the parameterizations by linguistic hedges used in earlier approaches. We
formalize the general parameterizations, propose bivalent and graded notions of
semantic entailment of fuzzy attribute implications, show their
characterization in terms of least models and complete axiomatization, and
provide characterization of bases of fuzzy attribute implications derived from
data.
| [
{
"version": "v1",
"created": "Sat, 25 Oct 2014 20:53:10 GMT"
}
] | 1,466,553,600,000 | [
[
"Vychodil",
"Vilem",
""
]
] |
1410.7063 | Sander Beckers | Sander Beckers and Joost Vennekens | Towards a General Framework for Actual Causation Using CP-logic | http://ceur-ws.org/Vol-1413/ | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Since Pearl's seminal work on providing a formal language for causality, the
subject has garnered a lot of interest among philosophers and researchers in
artificial intelligence alike. One of the most debated topics in this context
regards the notion of actual causation, which concerns itself with specific -
as opposed to general - causal claims. The search for a proper formal
definition of actual causation has evolved into a controversial debate, that is
pervaded with ambiguities and confusion. The goal of our research is twofold.
First, we wish to provide a clear way to compare competing definitions. Second,
we also want to improve upon these definitions so they can be applied to a more
diverse range of instances, including non-deterministic ones. To achieve these
goals we will provide a general, abstract definition of actual causation,
formulated in the context of the expressive language of CP-logic (Causal
Probabilistic logic). We will then show that three recent definitions by Ned
Hall (originally formulated for structural models) and a definition of our own
(formulated for CP-logic directly) can be viewed and directly compared as
instantiations of this abstract definition, which allows them to deal with a
broader range of examples.
| [
{
"version": "v1",
"created": "Sun, 26 Oct 2014 17:30:36 GMT"
},
{
"version": "v2",
"created": "Thu, 27 Nov 2014 15:57:58 GMT"
},
{
"version": "v3",
"created": "Thu, 29 Oct 2015 14:05:54 GMT"
}
] | 1,446,163,200,000 | [
[
"Beckers",
"Sander",
""
],
[
"Vennekens",
"Joost",
""
]
] |
1410.7223 | Felix Diaz Hermida | Felix Diaz-Hermida, Alberto Bugarin, David E. Losada | The probatilistic Quantifier Fuzzification Mechanism FA: A theoretical
analysis | 58 pages, 1 figure | null | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The main goal of this work is to analyze the behaviour of the FA quantifier
fuzzification mechanism. As we prove in the paper, this model has a very solid
theorethical behaviour, superior to most of the models defined in the
literature. Moreover, we show that the underlying probabilistic interpretation
has very interesting consequences.
| [
{
"version": "v1",
"created": "Mon, 27 Oct 2014 13:12:43 GMT"
}
] | 1,414,454,400,000 | [
[
"Diaz-Hermida",
"Felix",
""
],
[
"Bugarin",
"Alberto",
""
],
[
"Losada",
"David E.",
""
]
] |
1410.7849 | Andrew Connor | A.M.Connor | A mutli-thread tabu search algorithm | null | Design Optimization: International Journal of Product and Process
Improvement, 1(3), 293-304, 1999 | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | This paper describes a novel refinement to a Tabu search algorithm that has
been implemented in an attempt to improve the robustness of the search when
applied to particularly complex problems. In this approach, two Tabu searches
are carried out in parallel. Each search thread is characterised by it's own
short term memory which forces that point out of local optima. However, the two
search threads share an intermediate term memory so allowing a degree of
information to be passed between them. Results are presented for both
unconstrained and constrained numerical functions as well as a problem in the
field of hydraulic circuit optimization. Simulation of hydraulic circuit
performance is achieved by linking the optimization algorithm to the commercial
simulation package Bathfp.
| [
{
"version": "v1",
"created": "Wed, 29 Oct 2014 01:04:58 GMT"
}
] | 1,414,627,200,000 | [
[
"Connor",
"A. M.",
""
]
] |
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