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inria-00625815, version 1

Random positions in Go

Benard Helmstetter 1, Chang-Shing Lee 2, Fabien Teytaud () 34, Olivier Teytaud () 34, Wang Mei-Hui 2, Shi-Jim Yen 5

Computational Intelligence and Games (2011)

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).

  • 1:  Laboratoire d'Informatique Avancée de Saint-Denis (LIASD)
  • Université Paris VIII - Vincennes Saint-Denis : EA4383
  • 2:  Department of Computer Science and Information Engineering (CSIE)
  • National University of Tainan
  • 3:  Laboratoire de Recherche en Informatique (LRI)
  • CNRS : UMR8623 – Université Paris XI - Paris Sud
  • 4:  TAO (INRIA Saclay - Ile de France)
  • INRIA – CNRS : UMR8623 – Université Paris XI - Paris Sud
  • 5:  National Dong Hwa University (NDHU)
  • National Dong Hwa University
  • Domain : Computer Science/Computer Science and Game Theory
 
  • inria-00625815, version 1
  • oai:hal.inria.fr:inria-00625815
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  • Submitted on: Thursday, 22 September 2011 16:56:32
  • Updated on: Friday, 23 September 2011 10:23:02