J. Y. Audibert and S. Bubeck, Minimax policies for adversarial and stochastic bandits, Proceedings of the 22nd Annual Conference on Learning Theory, 2009.
URL : https://hal.archives-ouvertes.fr/hal-00834882

P. Auer, N. Cesa-bianchi, Y. Freund, and R. E. Schapire, The Nonstochastic Multiarmed Bandit Problem, SIAM Journal on Computing, vol.32, issue.1, pp.48-77, 2003.
DOI : 10.1137/S0097539701398375
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.130.158

J. Borsboom, J. Saito, G. Chaslot, and J. Uiterwijk, A comparison of Monte-Carlo methods for Phantom Go, Proc. 19th Belgian?Dutch Conference on Artificial Intelligence?BNAIC, 2007.

G. W. Brown, Iterative solution of games by fictitious play Activity analysis of production and allocation, pp.374-376, 1951.

T. Cazenave, A Phantom-Go program Advances in Computer Games, pp.120-125, 2006.

N. Cesa-bianchi and G. Lugosi, Prediction, learning, and games, 2006.
DOI : 10.1017/CBO9780511546921

P. Ciancarini and G. P. Favini, Monte carlo tree search techniques in the game of Kriegspiel, Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence (IJCAI-09), pp.474-479, 2009.

R. Coulom, Efficient Selectivity and Backup Operators in Monte-Carlo Tree Search, Proceedings of the 5th international conference on computers and games, pp.72-83, 2006.
DOI : 10.1007/978-3-540-75538-8_7
URL : https://hal.archives-ouvertes.fr/inria-00116992

D. Fudenberg and J. Tirole, Game Theory, 1991.