Document Type

Conference Proceeding

Publisher

IEEE

Faculty

Faculty of Computing, Health and Science

School

School of Computer and Information Science

RAS ID

5266

Comments

This is an Author's Accepted Manuscript of: Hingston, P. F. (2007). Evolving Players for an Ancient Game: Hnefetafl. Proceedings of IEEE Symposium on Computational Intelligence and Games. (pp. 168-174). Honolulu. IEEE. Available here

© 2007 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Abstract

Hnefatafl is an ancient Norse game - an ancestor of chess. In this paper, we report on the development of computer players for this game. In the spirit of Blondie24, we evolve neural networks as board evaluation functions for different versions of the game. An unusual aspect of this game is that there is no general agreement on the rules: it is no longer much played, and game historians attempt to infer the rules from scraps of historical texts, with ambiguities often resolved on gut feeling as to what the rules must have been in order to achieve a balanced game. We offer the evolutionary method as a means by which to judge the merits of alternative rule sets

DOI

10.1109/CIG.2007.368094

Access Rights

free_to_read

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Link to publisher version (DOI)

10.1109/CIG.2007.368094