Toward a model op human game playing

Authors:
Marc Eisenstadt;Yaakov Kareev
Affiliations:
Department of Psychology, University of California, San Diego, La Jolla, California;Department of Psychology, University of California, San Diego, La Jolla, California
Venue:
IJCAI'73 Proceedings of the 3rd international joint conference on Artificial intelligence
Year:
1973

Citing 3
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AFIPS '71 (Fall) Proceedings of the November 16-18, 1971, fall joint computer conference

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Abstract

This paper presents an overview of a game playing model which is based on human perceptual and problem solving abilities. The representation of games, acquisition of rules, learning of strategies, and selection of moves are outlined. Details of move selection, includin scanning of the board, use of familiar patterns to suggest move candidates, evaluation of moves, and lookahead are described. Finally, there is a discussion of the means by which the model learns to play a better game.