Learning Middlegame Patterns in Chess: A Case Study.

KUBAT, Miroslav and Jan ŽIŽKA. Learning Middlegame Patterns in Chess: A Case Study. In Proceedings of the 13th International Conference on Industrial & Engineering Applications of AI & Expert Systems. New Orleans, LA, U.S.A.: Springer Verlag, 2000, p. 426-433. LNCS.

Basic information

Original name

Learning Middlegame Patterns in Chess: A Case Study.

Authors

KUBAT, Miroslav and Jan ŽIŽKA

Edition

New Orleans, LA, U.S.A. Proceedings of the 13th International Conference on Industrial & Engineering Applications of AI & Expert Systems, p. 426-433, LNCS, 2000

Publisher

Springer Verlag

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Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

20200 2.2 Electrical engineering, Electronic engineering, Information engineering

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

Organization unit

Faculty of Informatics

Keywords in English

machine learning; pattern recognition; computer chess

Tags

computer chess, machine learning, pattern recognition

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Abstract

V originále

Experiments with a program that learns to classify chessboard positions that permit the bishop sacrifice at h7. Discussed are some problems pertaining to the collection of training examples, their representation, and preclassification.