Combiner connaissances expertes, hors-ligne, transientes et en ligne pour l'exploration Monte-Carlo. Apprentissage et MC
暂无分享,去创建一个
Olivier Teytaud | Christophe Fiter | Julien Perez | Sylvain Gelly | Arpad Rimmel | Guillaume Chaslot | Jean-Baptiste Hoock | L. Chatriot
[1] R. Agrawal. The Continuum-Armed Bandit Problem , 1995 .
[2] Zoubin Ghahramani,et al. Proceedings of the 24th international conference on Machine learning , 2007, ICML 2007.
[3] H. Jaap van den Herik,et al. Progressive Strategies for Monte-Carlo Tree Search , 2008 .
[4] Sylvain Gelly,et al. Modifications of UCT and sequence-like simulations for Monte-Carlo Go , 2007, 2007 IEEE Symposium on Computational Intelligence and Games.
[5] Bruno Bouzy,et al. Monte-Carlo strategies for computer Go , 2006 .
[6] Bruno Bouzy,et al. Associating domain-dependent knowledge and Monte Carlo approaches within a Go program , 2005, Inf. Sci..
[7] Lin Wu,et al. SVM and pattern-enriched common fate graphs for the game of go , 2005, ESANN.
[8] Bruno Bouzy,et al. Bayesian Generation and Integration of K-nearest-neighbor Patterns for 19x19 Go , 2005, CIG.
[9] Denyse Baillargeon,et al. Bibliographie , 1929 .
[10] Peter Auer,et al. Finite-time Analysis of the Multiarmed Bandit Problem , 2002, Machine Learning.
[11] Rémi Coulom,et al. Efficient Selectivity and Backup Operators in Monte-Carlo Tree Search , 2006, Computers and Games.
[12] Rémi Munos,et al. Bandit Algorithms for Tree Search , 2007, UAI.
[13] Rémi Coulom,et al. Computing "Elo Ratings" of Move Patterns in the Game of Go , 2007, J. Int. Comput. Games Assoc..
[14] Thomas P. Hayes,et al. Robbing the bandit: less regret in online geometric optimization against an adaptive adversary , 2006, SODA '06.
[15] David Silver,et al. Combining online and offline knowledge in UCT , 2007, ICML '07.
[16] H. Robbins,et al. Asymptotically efficient adaptive allocation rules , 1985 .
[17] Csaba Szepesvári,et al. Bandit Based Monte-Carlo Planning , 2006, ECML.