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AAAI 1984

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

Conference Paper Learning Artificial Intelligence

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-tat-toe, go-moku, and chess. ’

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Keywords

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Context

Venue
AAAI Conference on Artificial Intelligence
Archive span
1980-2026
Indexed papers
28718
Paper id
347503584199289582