text: 68,109,1456601775444725761,780011537738174464,Dennis Soemers,"(1/5) Our new paper on ""Optimised Playout Implementations for the Ludii General Game System"" is now available on arXiv! <LINK> <LINK> (2/5) Based on the game descriptions in the game description language of @LudiiGames, we automatically detect whether games fit in any of a few broad classes of games that permit significant optimisations for (semi-)random playouts / rollouts (as used in e.g. MCTS) (3/5) One example is in games like Chess, where legal + illegal (due to some postcondition) moves (blue + red arrows) are cheap to compute, but filtering this down to only the legal (blue) moves is expensive. <LINK> (4/5) In rollouts, we sample moves (uniformly or otherwise) from the complete set, and only evaluate the expensive postconditions for moves that were sampled (rejecting them and resampling if postconditions are not satisfied). The same idea applies to liberty tests in Go. (5/5) This work will be presented at ACG 2021 in about two and a half weeks. Register for free at <LINK>! @LudiiGames @archaeoludology @UM_DKE @ERC_Research",https://arxiv.org/abs/2111.02839,"This paper describes three different optimised implementations of playouts, as commonly used by game-playing algorithms such as Monte-Carlo Tree Search. Each of the optimised implementations is applicable only to specific sets of games, based on their rules. The Ludii general game system can automatically infer, based on a game's description in its general game description language, whether any optimised implementations are applicable. An empirical evaluation demonstrates major speedups over a standard implementation, with a median result of running playouts 5.08 times as fast, over 145 different games in Ludii for which one of the optimised implementations is applicable. ",Optimised Playout Implementations for the Ludii General Game System,5,"['(1/5) Our new paper on ""Optimised Playout Implementations for the Ludii General Game System"" is now available on arXiv! <LINK> <LINK>', '(2/5) Based on the game descriptions in the game description language of @LudiiGames, we automatically detect whether games fit in any of a few broad classes of games that permit significant optimisations for (semi-)random playouts / rollouts (as used in e.g. MCTS)', '(3/5) One example is in games like Chess, where legal + illegal (due to some postcondition) moves (blue + red arrows) are cheap to compute, but filtering this down to only the legal (blue) moves is expensive. https://t.co/su59U36SFW', '(4/5) In rollouts, we sample moves (uniformly or otherwise) from the complete set, and only evaluate the expensive postconditions for moves that were sampled (rejecting them and resampling if postconditions are not satisfied). The same idea applies to liberty tests in Go.', '(5/5) This work will be presented at ACG 2021 in about two and a half weeks. Register for free at https://t.co/hPWDBa893J!\n\n@LudiiGames @archaeoludology @UM_DKE @ERC_Research']",21,11,1045