Applying adversarial planning techniques to Go

S. Willmott, J. Richardson, A. Bundy, J.M. Levine

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

Approaches to computer game playing based on alpha-beta search of the tree of possible move sequences combined with a position evaluation function have been successful for many games, notably Chess. Such approaches are less successful for games with large search spaces and complex positions, such as Go, and we are led to seek alternatives. One such alternative is to model the goals of the players, and their strategies for achieving these goals. This approach means searching the space of possible goal expansions, typically much smaller than the space of move sequences. Previous attempts to apply these techniques to Go have been unable to provide results for anything other than a high strategic level or very open game positions. In this paper we describe how adversarial hierarchical task network planning can provide a framework for goal-directed game playing in Go which is also applicable both strategic and tactical problems.
LanguageEnglish
Pages45-82
Number of pages37
JournalTheoretical Computer Science
Volume252
Issue number1
DOIs
Publication statusPublished - 2001

Fingerprint

Computer games
Function evaluation
Planning
Game
Network Planning
Computer Games
Alternatives
Evaluation Function
Search Space

Keywords

  • computer games
  • planning
  • adversarial planning
  • alpha-beta search

Cite this

Willmott, S. ; Richardson, J. ; Bundy, A. ; Levine, J.M. / Applying adversarial planning techniques to Go. In: Theoretical Computer Science. 2001 ; Vol. 252, No. 1. pp. 45-82.
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Applying adversarial planning techniques to Go. / Willmott, S.; Richardson, J.; Bundy, A.; Levine, J.M.

In: Theoretical Computer Science, Vol. 252, No. 1, 2001, p. 45-82.

Research output: Contribution to journalArticle

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