These keywords were added by machine and not by the authors. They show that while a few of the very top programs can apparently solve most of these evaluation problems in their playouts already, these problems are difficult to solve by global search. The results give a good indication of the state of the art in computer Go as of 2012/2013. Then, an extensive empirical study of ten leading Go programs investigates their performance in two specifically designed test sets containing two safe group and seki situations. Well known weaknesses of many programs include (1) the handling of several simultaneous fights, including the two safe groups problem, and (2) dealing with coexistence in seki.Īfter a brief review of MCTS techniques, three research questions regarding the behavior of MCTS-based Go programs in specific types of Go situations are formulated. Still, program performance is uneven - most current Go programs are much stronger in some aspects of the game, such as local fighting and positional evaluation, than in other aspects. ![]() Monte-Carlo Tree Search methods have led to huge progress in computer Go.
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