The X-0-0 heuristic in game tree analysis

  • Authors:
  • J. Denbigh Starkey

  • Affiliations:
  • Computer Science Department, Wahington State University, Pullman, Washington

  • Venue:
  • IJCAI'79 Proceedings of the 6th international joint conference on Artificial intelligence - Volume 2
  • Year:
  • 1979

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Abstract

Programs for two-person games, such as chess or Go, are heavily dependent on Minimax evaluation of large game trees, which is combined with heuristics in an attempt to prune these trees as severely as possible. In particular, alpha-beta pruning, usually combined with the killer heuristic, is used in all major minimax-based programs, In this paper we shall propose a new heuristic which could be incorporated into minimax-based programs, and which should significantly increase the pruning possible during the analysis of game trees. This new heuristic, which can be combined with alpha-beta and the killer heuristic, is called the X-0-0 heuristic. The development of the heuristic was prompted by the difficulty of analyzing large game trees in Go, and is based on a formalism and extension of the Go proverb "the enemy's play is my own key play".