inria-00544622, version 1
Current Frontiers in Computer Go
Arpad Rimmel 1Olivier Teytaud
2, 3Chang-Shing Lee 4Shi-Jim Yen a, 5Mei-Hui Wang 4Shang-Rong Tsai b, 6
IEEE Transactions on Computational Intelligence and Artificial Intelligence in Games (2010) in press
Résumé : This paper presents the recent technical advances in Monte-Carlo Tree Search for the Game of Go, shows the many similarities and the rare differences between the current best programs, and reports the results of the computer-Go event organized at FUZZ-IEEE 2009, in which four main Go programs played against top level humans. We see that in 9x9, computers are very close to the best human level, and can be improved easily for the opening book; whereas in 19x19, handicap 7 is not enough for the computers to win against top level professional players, due to some clearly understood (but not solved) weaknesses of the current algorithms. Applications far from the game of Go are also cited. Importantly, the first ever win of a computer against a 9th Dan professional player in 9x9 Go occurred in this event.
- a – Department of Computer Science and Information Engineering
- b – Chang-Jung Christian University
- 1 : Department of Computing Science
- Department of Computing Science, University of Alberta
- 2 : TAO (INRIA Saclay - Ile de France)
- INRIA – CNRS : UMR8623 – Université Paris XI - Paris Sud
- 3 : Laboratoire de Recherche en Informatique (LRI)
- CNRS : UMR8623 – Université Paris XI - Paris Sud
- 4 : Department of Computer Science and Information Engineering (CSIE)
- National University of Tainan
- 5 : National Dong Hwa University (NDHU)
- National Dong Hwa University
- 6 : Department of Information Management
- Chang Jung Christian University
- Domaine : Mathématiques/Optimisation et contrôle
- inria-00544622, version 1
- http://hal.inria.fr/inria-00544622
- oai:hal.inria.fr:inria-00544622
- Contributeur : Olivier Teytaud
- Soumis le : Jeudi 9 Décembre 2010, 10:08:20
- Dernière modification le : Jeudi 9 Décembre 2010, 22:10:30






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