ML Anthology

Constraint-Based Generalization: Learning Game-Playing Plans from Single Examples

Steven Minton
AAAI 1984 pp. 251-254
/aaai/1984/minton1984aaai-constraint/

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.

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Cite

Text

Minton. "Constraint-Based Generalization: Learning Game-Playing Plans from Single Examples." AAAI Conference on Artificial Intelligence, 1984.

Markdown

[Minton. "Constraint-Based Generalization: Learning Game-Playing Plans from Single Examples." AAAI Conference on Artificial Intelligence, 1984.](https://mlanthology.org/aaai/1984/minton1984aaai-constraint/)

BibTeX

@inproceedings{minton1984aaai-constraint,
  title     = {{Constraint-Based Generalization: Learning Game-Playing Plans from Single Examples}},
  author    = {Minton, Steven},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {1984},
  pages     = {251-254},
  url       = {https://mlanthology.org/aaai/1984/minton1984aaai-constraint/}
}