publication . Other literature type . Article . 1995

Temporal difference learning and TD-Gammon

G. Tesauro;
  • Published: 01 Mar 1995
  • Publisher: Association for Computing Machinery (ACM)
Abstract
Ever since the days of Shannon's proposal for a chess-playing algorithm [12] and Samuel's checkers-learning program [10] the domain of complex board games such as Go, chess, checkers, Othello, and backgammon has been widely regarded as an ideal testing ground for exploring a variety of concepts and approaches in artificial intelligence and machine learning. Such board games offer the challenge of tremendous complexity and sophistication required to play at expert level. At the same time, the problem inputs and performance measures are clear-cut and well defined, and the game environment is readily automated in that it is easy to simulate the board, the rules of ...
Subjects
ACM Computing Classification System: ComputingMilieux_PERSONALCOMPUTING
free text keywords: Sophistication, media_common.quotation_subject, media_common, Combinatorial game theory, Game theory, Stochastic game, Bitboard, Artificial intelligence, business.industry, business, Sequential game, Temporal difference learning, Game mechanics, Computer science, Computer Science (miscellaneous), Human-Computer Interaction, Computational Mechanics, Computer Graphics and Computer-Aided Design
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