Monte-carlo tree search: A New Framework for Game AI1

Belgian/Netherlands Artificial Intelligence Conference

Volumn , Issue , 2008, Pages 389-390

  Chaslot, Guillaume ^a   Bakkes, Sander ^a   Szitai, Istvan ^a   Spronck, Pieter ^a  

^a MAASTRICHT UNIVERSITY   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

HUMAN COMPUTER INTERACTION; MONTE CARLO METHODS;

BOARD GAMES; EVALUATION FUNCTION; GAME AI; MONTE-CARLO TREE SEARCHES; SEARCH SPACES; UNIFIED FRAMEWORK; VIDEO GAME;

ARTIFICIAL INTELLIGENCE;

EID: 78149337262     PISSN: 15687805     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (3)

1. Sander Bakkes and Pieter Spronck. AI Game Programming Wisdom 4, chapter Automatically Generating Score Functions for Strategy Games, pages 647-658. Charles River Media, Hingham, MA., U.S.A., 2008.
2. G.M.J-B. Chaslot, J-T. Saito, B. Bouzy, J.W.H.M. Uiterwijk, and H.J. van den Herik. Monte-Carlo Strategies for Computer Go. In Proceedings of the 18th Belgian-Dutch Conference on Artificial Intelligence, pages 83-90, 2006.
3. L. Kocsis and C. Szepesvári. Bandit Based Monte-Carlo Planning. In Machine Learning: ECML 2006, Lecture Notes in Artificial Intelligence 4212, pages 282-293, 2006.