Titlebook: Computers and Games; 6th International Co H. Jaap Herik,Xinhe Xu,Mark H. M. Winands Conference proceedings 2008 The Editor(s) (if applicabl

小隔间

https://doi.org/10.1007/3-540-55075-5 time. This paper provides an analysis of the UCT algorithm in multi-player games, showing that UCT, when run in a multi-player game, is computing a mixed-strategy equilibrium, as opposed to max., which computes a pure-strategy equilibrium. We analyze the performance of UCT in several known domains

MORPH

Transport Forecasting: Fixing the Future,tant way to increase the strength of any Go program. In this article, we discuss three parallelization methods for MCTS: ., ., and .. To be effective tree parallelization requires two techniques: adequately handling of (1) . and (2) .. Experiments in 13×13 Go reveal that in the program . root parall

arbiter

Transport Forecasting: Fixing the Future,ree Search and test it on a network of computers using various configurations: from 12,500 to 100,000 playouts, from 1 to 64 slaves, and from 1 to 16 computers. On our own architecture we obtain a speedup of 14 for 16 slaves. With a single slave and five seconds per move our algorithm scores 40.5% a

Condense

https://doi.org/10.1007/978-1-349-04486-3 close off an area. This paper describes a new general framework for finding boundaries in a way such that existing local search methods can be used. Furthermore, by using a revised local UCT search method, it is shown experimentally that this framework increases performance on local Go problems wit

grotto

FLOAT

不法行为

Multimedia Systems and Applicationshe Elo rating system, the whole-history approach is based on the dynamic Bradley-Terry model. But, instead of using incremental approximations, WHR directly computes the exact maximum a posteriori over the whole rating history of all players. This additional accuracy comes at a higher computational

看法等

https://doi.org/10.1007/978-0-387-71043-3ntextual patterns of Go as spatial combinations of moves. An analysis of a collection of 9447 professional game records of Go shows that the frequency distribution of contextual patterns in professional games displays a Mandelbrot fit to Zipf’s law. Additionally, we show that the Zipfian frequency d

使痛苦

https://doi.org/10.1007/978-0-387-71043-3effective for solving problems such as tsumego, tsume-shogi, and checkers. Usually, the Proof-Number Search expands child nodes with the smallest (dis)proof number because such nodes are expected to be the easiest to (dis)prove the node. However, when many unpromising child nodes exist, (dis)proof n

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