R. Coulom, Efficient selectivity and back-up operators in monte-carlo tree search, Proceedings of the 5th Conference on Computers and Games (CG'2006), pp.72-83, 2006.
DOI : 10.1007/978-3-540-75538-8_7
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.657.3216

R. Coulom, Computing Elo ratings of move patterns in the game of Go, ICGA Journal, vol.30, issue.4, pp.198-208, 2007.
URL : https://hal.archives-ouvertes.fr/inria-00149859

S. Gelly and D. Silver, Achieving master level play in 9 x 9 computer go, Proceedings of the 23rd national conference on Artifical Intelligence (AAAI'08), pp.1537-1540, 2008.

C. Lee, M. Müller, and O. Teytaud, Special Issue on Monte Carlo Techniques and Computer Go, IEEE Transactions on Computational Intelligence and AI in Games, vol.2, issue.4, pp.225-228, 2010.
DOI : 10.1109/TCIAIG.2010.2099154

A. Rimmel, O. Teytaud, C. Lee, S. Yen, M. Wang et al., Current Frontiers in Computer Go, IEEE Transactions on Computational Intelligence and AI in Games, vol.2, issue.4, pp.229-238, 2010.
DOI : 10.1109/TCIAIG.2010.2098876
URL : https://hal.archives-ouvertes.fr/inria-00544622

T. Cazenave and A. Saffidine, Utilisation de la recherche arborescente Monte-Carlo au Hex, Revue d'intelligence artificielle, vol.23, issue.2-3, pp.183-202, 2009.
DOI : 10.3166/ria.23.183-202

B. Arneson, R. B. Hayward, and P. Henderson, Monte Carlo Tree Search in Hex, IEEE Transactions on Computational Intelligence and AI in Games, vol.2, issue.4, pp.251-258, 2010.
DOI : 10.1109/TCIAIG.2010.2067212
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.297.2930

M. H. Winands, Y. Björnsson, and J. Saito, Monte Carlo Tree Search in Lines of Action, IEEE Transactions on Computational Intelligence and AI in Games, vol.2, issue.4, pp.239-250, 2010.
DOI : 10.1109/TCIAIG.2010.2061050

D. M. Breuker, Memory versus search in games, 1998.

B. E. Childs, J. H. Brodeur, and L. Kocsis, Transpositions and move groups in Monte Carlo tree search, 2008 IEEE Symposium On Computational Intelligence and Games, pp.389-395, 2008.
DOI : 10.1109/CIG.2008.5035667
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.154.7085

J. Méhat and T. Cazenave, Combining UCT and Nested Monte Carlo Search for Single-Player General Game Playing, IEEE Transactions on Computational Intelligence and AI in Games, vol.2, issue.4, pp.271-277, 2010.
DOI : 10.1109/TCIAIG.2010.2088123

L. Kocsis and C. Szepesvàri, Bandit Based Monte-Carlo Planning, Proceedings of the 17th European Conference on Machine Learning (ECML'06), pp.282-293, 2006.
DOI : 10.1007/11871842_29
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.102.1296

T. Cazenave, Nested monte-carlo search, Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI-09), pp.456-461, 2009.
DOI : 10.1109/ipdps.2009.5161122
URL : https://hal.archives-ouvertes.fr/hal-01436286

C. Browne and H. Strategy, Making the Right Connections, 2000.

P. Henderson, B. Arneson, and R. B. Hayward, Solving 8x8 Hex, Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI-09), pp.505-510, 2009.

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

M. Genesereth and N. Love, General Game Playing, Synthesis Lectures on Artificial Intelligence and Machine Learning, vol.8, issue.2, pp.62-72, 2005.
DOI : 10.2200/S00564ED1V01Y201311AIM024

A. Kishimoto and M. Müller, A general solution to the graph history interaction problem, Proceedings of the 19th national conference on Artifical Intelligence (AAAI'04), pp.644-649, 2004.