Temporal difference learning applied to game playing and the results of application to Shogi

@article{Beal2001TemporalDL,
  title={Temporal difference learning applied to game playing and the results of application to Shogi},
  author={D. F. Beal and M. Smith},
  journal={Theor. Comput. Sci.},
  year={2001},
  volume={252},
  pages={105-119}
}
  • D. F. Beal, M. Smith
  • Published 2001
  • Computer Science
  • Theor. Comput. Sci.
  • This paper describes the application of temporal difference (TD) learning to minimax searches in general, and presents results from shogi. TD learning is used to adjust the weights for evaluation features over the course of a series of games, starting from arbitrary initial values. For some games, to obtain weights accurate enough for high-performance play will require the TD learning phase to make use of minimax searches. A theoretical description of TD applied to minimax search is given, and… CONTINUE READING
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