Adding expert knowledge and exploration in Monte-Carlo tree search

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6048 LNCS, Issue , 2010, Pages 1-13

  Chaslot, Guillaume ^a   Fiter, Christophe ^b   Hoock, Jean Baptiste ^b   Rimmel, Arpad ^b   Teytaud, Olivier ^b  

^a MAASTRICHT UNIVERSITY   (Netherlands)

^b CNRS   (France)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER GO; DATA SETS; EXPERT KNOWLEDGE; EXPERT RULE; MONTE CARLO; MONTE CARLO SIMULATION; RECENT PROGRESS; TREE SEARCH;

COMPUTER SOFTWARE;

EID: 77953762833     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-12993-3_1     Document Type: Conference Paper

References (14)

1. Chaslot, G.M.J.B., Winands, M.H.M., Uiterwijk, J.W.H.M., van den Herik, H.J., Bouzy, B.: Progressive strategies for monte-carlo tree search. In: Wang, P., et al. (eds.) Proceedings of the 10th Joint Conference on Information Sciences (JCIS 2007), pp. 655-661. World Scientific Publishing Co. Pte. Ltd., Singapore (2007)
2. Coulom, R.: Efficient selectivity and backup operators in monte-carlo tree search. In: Ciancarini, P., van den Herik, H.J. (eds.) CG 2006. LNCS, vol.4630, pp. 72-83. Springer, Heidelberg (2007)
3. Kocsis, L., Szepesvari, C.: Bandit-based monte-carlo planning. In: Fürnkranz, J., Scheffer, T., Spiliopoulou, M. (eds.) ECML 2006. LNCS (LNAI), vol.4212, pp. 282-293. Springer, Heidelberg (2006)
4. Gelly, S., Silver, D.: Combining online and offline knowledge in uct. In: ICML 2007: Proceedings of the 24th international conference on Machine learning, New York, NY, USA, pp. 273-280. ACM Press, New York (2007)
5. Brügmann, B.: Monte-Carlo Go (Unpublished) (1993)
6. Bouzy, B., Helmstetter, B.: Monte-Carlo Go developments. In: van den Herik, H.J., Iida, H., Heinz, E.A. (eds.) 10th Advances in Computer Games, pp. 159-174 (2003)
7. Coquelin, P.A., Munos, R.: Bandit algorithms for tree search. In: Proceedings of UAI 2007 (2007)
8. Gelly, S., Hoock, J.B., Rimmel, A., Teytaud, O., Kalemkarian, Y.: The parallelization of monte-carlo planning. In: Proceedings of the International Conference on Informatics in Control, Automation and Robotics (ICINCO 2008), pp. 198-203 (2008) (to appear)
9. Bouzy, B., Chaslot, G.M.J.B.: Bayesian generation and integration of k-nearestneighbor patterns for 19x19 go. In: Kendall, G., Lucas, S. (eds.) IEEE 2005 Symposium on Computational Intelligence in Games, Colchester, UK, pp. 176-181 (2005)
10. Coulom, R.: Computing elo ratings of move patterns in the game of go. In: Computer Games Workshop, Amsterdam, The Netherlands (2007)
11. Bouzy, B., Chaslot, G.M.J.B.: Monte-Carlo Go Reinforcement Learning Experiments. In: Kendall, G., Louis, S. (eds.) IEEE 2006 Symposium on Computational Intelligence in Games, Reno, USA, pp. 187-194 (2006)
12. Wang, Y., Gelly, S.: Modifications of UCT and sequence-like simulations for Monte- Carlo Go. In: IEEE Symposium on Computational Intelligence and Games, Honolulu, Hawaii, pp. 175-182 (2007)
13. Bouzy, B.: Associating domain-dependent knowledge and Monte-Carlo approaches within a go program. In: Chen, K. (ed.) Information Sciences, Heuristic Search and Computer Game Playing IV, vol.175, pp. 247-257 (2005)
14. Ralaivola, L., Wu, L., Baldi, P.: SVM and pattern-enriched common fate graphs for the game of Go. In: Proceedings of ESANN 2005, pp. 485-490 (2005)