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Move-Pruning Techniques for Monte-Carlo Go

  • Bruno Bouzy
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4250)

Abstract

Progressive Pruning (PP) is employed in the Monte-Carlo Go-playing program Indigo. For each candidate move, PP launches random games starting with this move. The goal of PP is: (1) to gather statistics on moves, and (2) to prune moves statistically inferior to the best one [7]. This papers yields two new pruning techniques: Miai Pruning (MP) and Set Pruning (SP). In MP the second move of the random games is selected at random among the set of candidate moves. SP consists in gathering statistics about two sets of moves, good and bad, and it prunes the latter when statistically inferior to the former. Both enhancements clearly speed up the process of selecting a move on 9×9 boards, and MP improves slightly the playing level. Scaling up MP to 19×19 boards results in a 30% speed-up enhancement and in a four-point improvement on average.

Keywords

Computer Game Relative Speed Good Move Pruning Technique Candidate Move 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Bruno Bouzy
    • 1
  1. 1.UFR de mathematiques et d’informatiqueUniversité René DescartesParisFrance

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