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Author Szepesvári, Csaba ♦ Sebag, Michèle ♦ Schoenauer, Marc ♦ Silver, David ♦ Teytaud, Olivier ♦ Kocsis, Levente ♦ Gelly, Sylvain
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Language English
Abstract The ancient oriental game of Go has long been considered a grand challenge for artificial intelligence. For decades, computer Go has defied the classical methods in game tree search that worked so successfully for chess and checkers. However, recent play in computer Go has been transformed by a new paradigm for tree search based on Monte-Carlo methods. Programs based on Monte-Carlo tree search now play at human-master levels and are beginning to challenge top professional players. In this paper, we describe the leading algorithms for Monte-Carlo tree search and explain how they have advanced the state of the art in computer Go.
Description Affiliation: EPC TAO, INRIA Saclay & LRI, Orsay, France (Gelly, Sylvain; Schoenauer, Marc; Sebag, Michèle; Teytaud, Olivier) || University College London, London, U.K. (Silver, David) || University of Alberta, Edmonton, Canada (Szepesvári, Csaba) || MTA SZTAKI, Budapest, Hungary (Kocsis, Levente)
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2005-08-01
Publisher Place New York
Journal Communications of the ACM (CACM)
Volume Number 55
Issue Number 3
Page Count 8
Starting Page 106
Ending Page 113

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Source: ACM Digital Library