H. Baier and P. Drake, The Power of Forgetting: Improving the Last-Good-Reply Policy in Monte Carlo Go, IEEE Transactions on Computational Intelligence and AI in Games, vol.2, issue.4, pp.303-309, 2010.
DOI : 10.1109/TCIAIG.2010.2100396

A. Bourki, G. Chaslot, M. Coulm, V. Danjean, H. Doghmen et al., Scalability and Parallelization of Monte-Carlo Tree Search, Proceedings of Advance in Computer Games, 2010.
DOI : 10.1007/978-3-642-17928-0_5

URL : https://hal.archives-ouvertes.fr/inria-00512854

G. Chaslot, C. Fiter, J. Hoock, A. Rimmel, and O. Teytaud, Adding expert knowledge and exploration in Monte-Carlo Tree Search Advances in Computer Games pp, pp.1-13, 2010.

R. Coulom, Computing Elo Ratings of Move Patterns in the Game of Go, Computer Games Workshop, 2007.
URL : https://hal.archives-ouvertes.fr/inria-00149859

R. Coulom, Efficient Selectivity and Backup Operators in Monte-Carlo Tree Search. Computers and Games pp, pp.72-83, 2007.
URL : https://hal.archives-ouvertes.fr/inria-00116992

P. Drake, The Last-Good-Reply Policy for Monte-Carlo Go, ICGA Journal, vol.32, issue.4, pp.221-227, 2009.
DOI : 10.3233/ICG-2009-32404

M. Enzenberger, M. Muller, B. Arneson, and R. Segal, Fuego—An Open-Source Framework for Board Games and Go Engine Based on Monte Carlo Tree Search, IEEE Transactions on Computational Intelligence and AI in Games, vol.2, issue.4, pp.259-270, 2009.
DOI : 10.1109/TCIAIG.2010.2083662

S. Gelly, L. Kocsis, M. Schoenauer, M. Sebag, D. Silver et al., The grand challenge of computer Go, Communications of the ACM, vol.55, issue.3, pp.106-113, 2012.
DOI : 10.1145/2093548.2093574

URL : https://hal.archives-ouvertes.fr/hal-00695370

S. Gelly and D. Silver, Combining online and offline knowledge in UCT, Proceedings of the 24th international conference on Machine learning, ICML '07, pp.273-280, 2007.
DOI : 10.1145/1273496.1273531

URL : https://hal.archives-ouvertes.fr/inria-00164003

S. Gelly and D. Silver, Monte-Carlo tree search and rapid action value estimation in computer Go, Artificial Intelligence, vol.175, issue.11, 2011.
DOI : 10.1016/j.artint.2011.03.007

T. Graepel, M. Goutrie, M. Krüger, and R. Herbrich, Learning on Graphs in the Game of Go, Artificial Neural Networks?ICANN, pp.347-352, 2001.
DOI : 10.1007/3-540-44668-0_49

A. M. Helmut, Board Representations for Neural Go Players Learning by Temporal Difference, Computational Intelligence and Games CIG 2007. IEEE Symposium on, pp.183-188, 2007.

J. Hoock, C. Lee, A. Rimmel, F. Teytaud, M. Wang et al., Intelligent Agents for the Game of Go, IEEE Computational Intelligence Magazine, vol.5, issue.4, pp.28-42, 2010.
DOI : 10.1109/MCI.2010.938360

URL : https://hal.archives-ouvertes.fr/inria-00544758

S. Huang, R. Coulom, and S. Lin, Monte-Carlo Simulation Balancing in Practice. Computers and Games pp, pp.81-92, 2011.

L. Kocsis and C. Szepesvári, Bandit Based Monte-Carlo Planning, Machine Learning: ECML, pp.282-293, 2006.
DOI : 10.1007/11871842_29

C. Lee, M. Wang, G. Chaslot, J. Hoock, A. Rimmel et al., The Computational Intelligence of MoGo Revealed in Taiwan's Computer Go Tournaments. Computational Intelligence and AI in Games, IEEE Transactions, pp.73-89, 2009.

A. Rimmel and F. Teytaud, Multiple Overlapping Tiles for Contextual Monte Carlo Tree Search. Applications of Evolutionary Computation pp, pp.201-210, 2010.
URL : https://hal.archives-ouvertes.fr/inria-00456422

A. Rimmel, F. Teytaud, and O. Teytaud, Biasing Monte-Carlo Simulations through RAVE Values. Computers and Games pp, pp.59-68, 2011.
URL : https://hal.archives-ouvertes.fr/inria-00485555

D. Silver, R. Sutton, and M. Müller, Temporal-difference search in computer Go, Machine Learning, vol.3, issue.1, pp.1-37, 2012.
DOI : 10.1007/s10994-012-5280-0

D. Stern, R. Herbrich, and T. Graepel, Bayesian pattern ranking for move prediction in the game of Go, Proceedings of the 23rd international conference on Machine learning , ICML '06, pp.873-880, 2006.
DOI : 10.1145/1143844.1143954

Y. Wang and S. Gelly, Modifications of UCT and sequence-like simulations for Monte-Carlo Go, 2007 IEEE Symposium on Computational Intelligence and Games, pp.175-182, 2007.
DOI : 10.1109/CIG.2007.368095