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 第6回講演会
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・第6回招待講演会
開催日：2009年1月27日（土）18時から19時半まで
場所：電気通信大学 西９号館３階ＡＶホール
参加無料（事前申し込み不要）
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講演者：Remi Coulom氏（シャルルドゴール大学；CrazyStone作者）
講演１：Criticality: a Monte-Carlo Heuristic for Go
Programs
abstract：When applying Monte-Carlo tree search in a Go-playing program, a variety of playout statistics can be used to guide the search. All-moves-as-first value, average score, or average point owner, in addition to winning frequency, provide useful information for the search algorithm. Criticality is another Monte-Carlo heuristic that estimates how important it is to own a point in order to win playouts. It was used succesfully as a pattern feature in Crazy Stone.
講演２：Local Quadratic Logistic Regression for Stochastic Optimization of Parameters
abstract: An important aspect of improving a game-playing program is the optimization of parameters from the observation of game outcomes. When the outcome of a game is binary (win/loss) or ternary (win/draw/loss), it provides a very noisy estimate of program strength. Estimating the probability of winning requires playing a very large number of games, and takes a lot of CPU time. Local Quadratic Logistic Regression is an efficient method to perform parameter optimization. It consists in fitting a quadratic response-surface model to the performance data. A statistical test of quadraticity is used to restrict this regression to a neighborhood of the optimal parameters. Extensive empirical testing with artificial functions demonstrates fast convergence. This method was used successfully to tune some parameters of Crazy Stone.
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