Title :
Evolving Players for an Ancient Game: Hnefatafl
Author :
Hingston, Philip
Author_Institution :
Sch. of Comput. & Inf. Sci., Edith Cowan Univ., Churchlands, WA
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
Keywords :
evolutionary computation; games of skill; neural nets; Hnefatafl; ancient Norse game; ancient game; board evaluation functions; board game; chess; evolutionary method; neural network; Artificial intelligence; Competitive intelligence; Computational intelligence; Evolutionary computation; Humans; Information science; Instruments; Neural networks; Evolution; Hnefatafl; board games;
Conference_Titel :
Computational Intelligence and Games, 2007. CIG 2007. IEEE Symposium on
Conference_Location :
Honolulu, HI
Print_ISBN :
1-4244-0709-5
DOI :
10.1109/CIG.2007.368094