Accessibility navigation


Chess endgame news: an Endgame challenge for neural nets

Haworth, G. (2019) Chess endgame news: an Endgame challenge for neural nets. ICGA Journal, 41 (3). p. 176. ISSN 1389-6911

[img]
Preview
Text - Accepted Version
· Please see our End User Agreement before downloading.

215kB
[img]
Preview
Text - Accepted Version
· Please see our End User Agreement before downloading.

520kB

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.3233/ICG-190109

Abstract/Summary

This article defines the challenge of training neural-networks on specific chess endgames and benchmarking their efficacy against the existing sub-8-man endgame tables. The key tasks are to measure how well they play and to infer higher-order rules and guidelines for play from them.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Computer Science
ID Code:86555
Uncontrolled Keywords:AlphaZero, ANN, Artificial Neural Network, Breakout, chess endgame, Deep Mind, EGT, Leela Chess Zero, MCTS, Shannon
Publisher:The International Computer Games Association

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation