D 2003

Learning Representative Patterns From Real Chess Positions: A Case Study

ŽIŽKA, Jan and Michal MÁDR

Basic information

Original name

Learning Representative Patterns From Real Chess Positions: A Case Study

Authors

ŽIŽKA, Jan (203 Czech Republic, guarantor) and Michal MÁDR (203 Czech Republic)

Edition

Hyderabad, India, Proceedings of the First Indian International Conference on Artificial Intelligence (IICAI-03), p. 1374-1387, 14 pp. 2003

Publisher

IICAI-03

Other information

Language

English

Type of outcome

Proceedings paper

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

India

Confidentiality degree

is not subject to a state or trade secret

RIV identification code

RIV/00216224:14330/03:00009152

Organization unit

Faculty of Informatics

ISBN

0-9727412-0-8

Keywords in English

pattern recognition; decision trees; classification; representation of examples; relevant attributes
Changed: 8/9/2004 16:36, doc. Ing. Jan Žižka, CSc.

Abstract

V originále

This paper deals with a particular pattern recognition by machine learning. The patterns are specific chess positions. A computer learns if a special pattern leads to a winning or losing game, i.e., a classification task based on real results and examples. As a learning algorithm, decision trees generated by the program C5/See5, also with boosting, were used. This algorithm does not employ chess rules or calculations of positions, it just learns from a selected set of 450 training positive and negative examples with 8 different representations of real positions played by human players. The most accurate classification reaches 92.98% for the combination of automatically generated trivial descriptions of positions (64 attributes) with expert descriptions suggested by humans (92 attributes).

Links

MSM 143300003, plan (intention)
Name: Interakce člověka s počítačem, dialogové systémy a asistivní technologie
Investor: Ministry of Education, Youth and Sports of the CR, Human-computer interaction, dialog systems and assistive technologies