Monte-carlo tree search: A new framework for game ai

Proceedings of the 4th Artificial Intelligence and Interactive Digital Entertainment Conference, AIIDE 2008

Volumn , Issue , 2008, Pages 216-217

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

^a MAASTRICHT UNIVERSITY   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

DOMAIN KNOWLEDGE; GAME AI; HIGH QUALITY; MONTE-CARLO TREE SEARCHES; SEARCH SPACES; UNIFIED FRAMEWORK; VIDEO GAME;

ARTIFICIAL INTELLIGENCE;

HUMAN COMPUTER INTERACTION;

EID: 77955681360     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (5)

1. Bakkes, S., and Spronck, P. 2008. AI Game Programming Wisdom 4. Charles River Media, Hingham, MA., U.S.A. chapter Automatically Generating Score Functions for Strategy Games, 647-658.
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3. Chaslot, G.-B.; Saito, J.-T.; Bouzy, B.; Uiterwijk, J.; and van den Herik, H. 2006. Monte-Carlo Strategies for Computer Go. In Proceedings of the 18th Belgian-Dutch Conference on Artificial Intelligence, 83-90.
4. Kocsis, L., and Szepesvari, C. 2006. Bandit Based Monte- Carlo Planning. In Machine Learning: ECML 2006, Lecture Notes in Artificial Intelligence 4212, 282-293.
5. Sheppard, B. 2002. World-championship-caliber scrabble. Artificial Intelligence 134(1):241-275.