Temporal Difference Learning for Heuristic Search and Game Playing

  title={Temporal Difference Learning for Heuristic Search and Game Playing},
  author={D. F. Beal and M. Smith},
  journal={Inf. Sci.},
  • D. F. Beal, M. Smith
  • Published 2000
  • Computer Science
  • Inf. Sci.
  • Abstract Temporal difference (TD) learning is a natural method of reinforcement learning that is particularly appropriate for learning in heuristic search and game playing. Sutton [Machine Learning 3 (1988) 9–44] introduced the TD(λ) method which is an elegant integration of supervised learning with TD learning. TD(λ) enabled Tesauro’s backgammon program to reach world championship standard. But it can be slow. Tesauro’s program was trained on 1 500 000 games. Recent work [D.F. Beal, M.C. Smith… CONTINUE READING
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