Open AccessProceedings Article
Constraint-based generalization: learning game-playing plans from single examples
Steven Minton
- pp 251-254
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It is shown how this technique can be used for learning tactical combinations in games and an implementation which learns forced wins in tic-tac-toe, go-moku, and chess is discussed.Abstract:
Constraint-based Generalization is a technique for deducing generalizations from a single example. We show how this technique can be used for learning tactical combinations in games and discuss an implementation which learns forced wins in tic-tac-toe, go-moku, and chess.read more
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