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We present three parallel algorithms for UCT. For 9×9 Go, they all improve the results of the programs that use them against GNU GO 3.6. The simplest one, the single-run algorithm, uses very few communications and shows improvements comparable to the more complex ones. Further improvements may be possible sharing more information in the multiple-runs(More)
Many problems have a huge state space and no good heuristic to order moves so as to guide the search toward the best positions. Random games can be used to score positions and evaluate their interest. Random games can also be improved using random games to choose a move to try at each step of a game. Nested Monte-Carlo Search addresses the problem of(More)
and WOLVE competed in previous Olympiads. A fifth program, BITaHex from China, registered but was unable to participate due to visa problems related to the recent dispute between Japan and China. MIMHEX is a Monte Carlo tree search program developed as part of a course taught by Pawlewicz and Lew on AI and Games in the Faculty of Mathematics, Informatics,(More)
Knowledge about forced moves enables to select a small number of moves from the set of possible moves. It is very important in complex domains where search trees have a large branching factor. Knowing forced moves drastically cuts the search trees. We propose a language and a metaprogram to create automatically the knowledge about interesting and forced(More)
We have parallelized our general game player Ary on a cluster of computers. We propose multiple par-allelization algorithms. For the sake of simplicity all our algorithms have processes that run independently and that join their results at the end of the thinking time in order to choose a move. Parallelization works very well for checkers, quite well for(More)
—Monte-Carlo tree search has recently been very successful for game playing particularly for games where the evaluation of a state is difficult to compute, such as Go or General Games. We compare Nested Monte-Carlo Search (NMC), Upper Confidence bounds for Trees (UCT-T), UCT with transposition tables (UCT+T) and a simple combination of NMC and UCT+T (MAX)(More)