DocumentCode :
3477110
Title :
Random positions in Go
Author :
Helmstetter, B. ; Chang-Shing Lee ; Teytaud, Fabien ; Teytaud, Olivier ; Mei-Hui Wang ; Yen, Shi-Jim
Author_Institution :
LIASD, Univ. Paris 8, Paris, France
fYear :
2011
fDate :
Aug. 31 2011-Sept. 3 2011
Firstpage :
250
Lastpage :
257
Abstract :
It is known that in chess, random positions are harder to memorize for humans. We here reproduce these experiments in the Asian game of Go, in which computers are much weaker than humans. We survey families of positions, discussing the relative strength of humans and computers, and then experiment random positions. The result is that computers are at the best amateur level for random positions. We also provide a protocol for generating interesting random positions (avoiding unfair situations).
Keywords :
computer games; Go; computers; humans; random position generation; Computational intelligence; Computers; Conferences; Games; Humans; Monte Carlo methods; Sections;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Games (CIG), 2011 IEEE Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4577-0010-1
Electronic_ISBN :
978-1-4577-0009-5
Type :
conf
DOI :
10.1109/CIG.2011.6032014
Filename :
6032014
Link To Document :
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