Monte-Carlo simulation balancing in practice

Shih Chieh Huang, Rémi Coulom, Shun Shii Lin

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

28 Citations (Scopus)

Abstract

Simulation balancing is a new technique to tune parameters of a playout policy for a Monte-Carlo game-playing program. So far, this algorithm had only been tested in a very artificial setting: it was limited to 5x5 and 6x6 Go, and required a stronger external program that served as a supervisor. In this paper, the effectiveness of simulation balancing is demonstrated in a more realistic setting. A state-of-the-art program, Erica, learned an improved playout policy on the 9x9 board, without requiring any external expert to provide position evaluations. The evaluations were collected by letting the program analyze positions by itself. The previous version of Erica learned pattern weights with the minorization-maximization algorithm. Thanks to simulation balancing, its playing strength was improved from a winning rate of 69% to 78% against Fuego 0.4.

Original languageEnglish
Title of host publicationComputers and Games - 7th International Conference, CG 2010, Revised Selected Papers
PublisherSpringer Verlag
Pages81-92
Number of pages12
ISBN (Print)3642179274, 9783642179273
DOIs
Publication statusPublished - 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6515 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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    Huang, S. C., Coulom, R., & Lin, S. S. (2011). Monte-Carlo simulation balancing in practice. In Computers and Games - 7th International Conference, CG 2010, Revised Selected Papers (pp. 81-92). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6515 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-642-17928-0_8