The grand challenge of computer Go

Author:

Gelly Sylvain1,Kocsis Levente2,Schoenauer Marc1,Sebag Michèle1,Silver David3,Szepesvári Csaba4,Teytaud Olivier1

Affiliation:

1. EPC TAO, INRIA Saclay & LRI, Orsay, France

2. MTA SZTAKI, Budapest, Hungary

3. University College London, London, U.K.

4. University of Alberta, Edmonton, Canada

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.

Funder

Seventh Framework Programme

Sixth Framework Programme

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science

Reference25 articles.

1. Carlo techniques and computer Go. In C.-S. Lee, M. Müller, and O. Teytaud, eds;Special;IEEE Trans. Comput. Intell. AI in Games,2010

2. Expected-outcome: a general model of static evaluation

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