Time management for Monte-Carlo tree search applied to the game of Go

Shih Chieh Huang, Remi Coulom, Shun Shii Lin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

Abstract

Monte-Carlo tree search (MCTS) is a new technique that has produced a huge leap forward in the strength of Go-playing programs. An interesting aspect of MCTS that has been rarely studied in the past is the problem of time management. This paper presents the effect on playing strength of a variety of time-management heuristics for 19 × 19 Go. Results indicate that clever time management can have a very significant effect on playing strength. Experiments demonstrate that the most basic algorithm for sudden-death time controls (dividing the remaining time by a constant) produces a winning rate of 43.2±2.2% against GNU Go 3.8 Level 2, whereas our most efficient time-allocation strategy can reach a winning rate of 60±2.2% without pondering and 67.4±2.1% with pondering.

Original languageEnglish
Title of host publicationProceedings - International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2010
Pages462-466
Number of pages5
DOIs
Publication statusPublished - 2010 Dec 1
Event2010 15th Conference on Technologies and Applications of Artificial Intelligence, TAAI 2010 - Hsinchu, Taiwan
Duration: 2010 Nov 182010 Nov 20

Publication series

NameProceedings - International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2010

Other

Other2010 15th Conference on Technologies and Applications of Artificial Intelligence, TAAI 2010
Country/TerritoryTaiwan
CityHsinchu
Period2010/11/182010/11/20

Keywords

  • Game of Go
  • Monte-Carlo tree search
  • Time management

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computational Theory and Mathematics

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