Learning a Game Strategy Using Pattern-Weights and Self-play
نویسندگان
چکیده
This paper demonstrates the use of pattern-weights in order to develop a strategy for an automated player of a non-cooperative version of the game of Diplomacy. Diplomacy is a multi-player, zerosum and simultaneous move game with imperfect information. Patternweights represent stored knowledge of various aspects of a game that are learned through experience. An automated computer player is developed without any initial strategy and is able to learn important strategic aspects of the game through self-play by storing pattern-weights and using temporal difference learning.
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