To create intelligent adaptive game opponent by using monte-carlo for tree search

5th International Conference on Natural Computation, ICNC 2009

Volumn 5, Issue , 2009, Pages 603-607

  Yang, Jiajian ^a   Gao, Yuan ^a   He, Suoju ^a   Liu, Xiao ^a   Fu, Yiwen ^a   Chen, Yang ^a   Ji, Donglin ^a  

^a BEIJING UNIVERSITY OF POSTS AND TELECOMMUNICATIONS   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ANN (ARTIFICIAL NEURAL NETWORK); BASIC PRINCIPLES; CHALLENGE LEVELS; COMPUTER GO; MONTE CARLO; NON-PLAYER CHARACTER; TREE SEARCH; VIDEO GAME;

COMPUTATIONAL EFFICIENCY; TREES (MATHEMATICS);

NEURAL NETWORKS;

EID: 77950560383     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICNC.2009.710     Document Type: Conference Paper

References (8)

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3. Peter Bentley Artical LETTING STONES GO UNTURNED, Feb, 2008.
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5. Sutton R.S. Reinforcement learning. An introduction. 2005
6. Monte Carlo method, Wikipedia, Retrieved from http://en.wikipedia.org/ wiki/Monte-Carlo-method (03/08/09).
7. Levente Kocsis and Csaba Szepesv'ari. Bandit based monte-carlo planning. In 15th European Conference on Machine Learning (ECML), pages 282-293, 2006.
8. Suoju He, Fan Xie, Yi Wang, Jin Meng, Hongtao Chen, Zhiqing Liu, Qiliang Zhu. Game Player Strategy Pattern Recognition and How UCT Algorithms Apply Pre-Knowledge of Player's Strategy to Improve Opponent AI. In the International Conference on Innovation in Software Engineering (ISE'2008), 2008.