R. Coulom, Efficient Selectivity and Backup Operators in Monte-Carlo Tree Search, Proceedings of the 5th International Conference on Computers and Games, 2006.
DOI : 10.1007/978-3-540-75538-8_7

URL : https://hal.archives-ouvertes.fr/inria-00116992

G. Chaslot, J. Saito, B. Bouzy, J. W. Uiterwijk, and H. J. Van-den-herik, Monte-Carlo Strategies for Computer Go, Proceedings of the 18th BeNeLux Conference on Artificial Intelligence, pp.83-91, 2006.

L. Kocsis and C. Szepesvari, Bandit Based Monte-Carlo Planning, 15th European Conference on Machine Learning (ECML), pp.282-293, 2006.
DOI : 10.1007/11871842_29

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.102.1296

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

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

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

F. Teytaud and O. Teytaud, Creating an Upper-Confidence-Tree Program for Havannah, pp.73-89, 2009.
DOI : 10.1007/978-3-642-12993-3_7

URL : https://hal.archives-ouvertes.fr/inria-00380539

S. Sharma, Z. Kobti, and S. Goodwin, Knowledge Generation for Improving Simulations in UCT for General Game Playing, AI '08: Proceedings of the 21st Australasian Joint Conference on Artificial Intelligence, pp.49-55, 2008.
DOI : 10.1023/A:1013689704352

P. Rolet, M. Sebag, and O. Teytaud, Optimal active learning through billiards and upper confidence trees in continous domains, Proceedings of the ECML conference, 2009.

F. De-mesmay, A. Rimmel, Y. Voronenko, and M. Püschel, Bandit-based optimization on graphs with application to library performance tuning, Proceedings of the 26th Annual International Conference on Machine Learning, ICML '09, 2009.
DOI : 10.1145/1553374.1553468

URL : https://hal.archives-ouvertes.fr/inria-00379523

P. Audouard, G. Chaslot, J. Hoock, J. Perez, A. Rimmel et al., Grid Coevolution for Adaptive Simulations: Application to the Building of Opening Books in the Game of Go, Proceedings of EvoGames, pp.323-332, 2009.
DOI : 10.1007/978-3-642-01129-0_36

URL : https://hal.archives-ouvertes.fr/inria-00369783

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

S. Gelly, J. B. Hoock, A. Rimmel, O. Teytaud, and Y. Kalemkarian, The parallelization of Monte-Carlo planning, Proceedings of the International Conference on Informatics in Control, Automation and Robotics, pp.198-203, 2008.
URL : https://hal.archives-ouvertes.fr/inria-00287867

M. Enzenberger and M. Müller, A Lock-Free Multithreaded Monte-Carlo Tree Search Algorithm, Proceedings of Advances in Computer Games 12, 2009.
DOI : 10.1007/978-3-642-12993-3_2

R. Coulom, Lockless hash table and other parallel search ideas, 2008.

T. Cazenave and N. Jouandeau, On the parallelization of UCT, Proceedings of CGW07, pp.93-101, 2007.

H. Kato and I. Takeuchi, Parallel Monte-Carlo Tree Search with Simulation Servers, 2010 International Conference on Technologies and Applications of Artificial Intelligence, 2008.
DOI : 10.1109/TAAI.2010.83

G. Chaslot, M. Winands, J. Uiterwijk, H. Van-den-herik, and B. Bouzy, Progressive Strategies for Monte-Carlo Tree Search, Proceedings of the 10th Joint Conference on Information Sciences, pp.655-661, 2007.

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. Pamplona Espagne, 2009.
DOI : 10.1007/978-3-642-12993-3_1

URL : https://hal.archives-ouvertes.fr/inria-00386477

R. Hunter, Nakade & ishi-no-shita, British Go journal, vol.128, pp.8-12, 2002.

T. Cazenave and B. Helmstetter, Combining tactical search and monte-carlo in the game of go, IEEE CIG, pp.171-175, 2005.

A. Moreno, A. Valls, D. Isern, and D. Sanchez, Applying Agent Technology to Healthcare: The GruSMA Experience, IEEE Intelligent Systems, vol.21, issue.6, pp.63-67, 2006.
DOI : 10.1109/MIS.2006.108

C. S. Lee and M. H. Wang, Ontology-based computational intelligent multi-agent and its application to CMMI assessment, Applied Intelligence, vol.20, issue.3, pp.203-219, 2009.
DOI : 10.1007/s10489-007-0071-1

B. Orgun and J. Vu, HL7 ontology and mobile agents for interoperability in heterogeneous medical information systems, Computers in Biology and Medicine, vol.36, issue.7-8, pp.817-836, 2006.
DOI : 10.1016/j.compbiomed.2005.04.010

C. S. Lee, M. H. Wang, and J. J. Chen, Ontology-based intelligent decision support agent for CMMI project monitoring and control, International Journal of Approximate Reasoning, vol.48, issue.1, pp.62-76, 2008.
DOI : 10.1016/j.ijar.2007.06.007

M. H. Wang, C. S. Lee, K. L. Hsieh, C. Y. Hsu, G. Acampora et al., Ontology-based multi-agents for intelligent healthcare applications, Journal of Ambient Intelligence and Humanized Computing, vol.36, issue.3, pp.111-131, 2010.
DOI : 10.1007/s12652-010-0011-5

V. Mnih, C. Szepesvári, and J. Audibert, Empirical Bernstein stopping, Proceedings of the 25th international conference on Machine learning, ICML '08, pp.672-679, 2008.
DOI : 10.1145/1390156.1390241

URL : https://hal.archives-ouvertes.fr/hal-00834983

J. Hoock and O. Teytaud, Bandit-Based Genetic Programming, Proceedings of EuroGP 2010, p.p. Accepted, 2010.
DOI : 10.1007/978-3-642-12148-7_23

URL : https://hal.archives-ouvertes.fr/inria-00452887

M. Lees, B. Logan, and G. K. Theodoropoulos, Agents, games and HLA, Simulation Modelling Practice and Theory, vol.14, issue.6, pp.752-767, 2006.
DOI : 10.1016/j.simpat.2005.10.007

J. Mendel, L. Zadeh, E. Trillas, R. Yager, L. Lawry et al., What Computing with Words Means to Me [Discussion Forum, IEEE Computational Intelligence Magazine, vol.5, issue.1, pp.20-26, 2010.
DOI : 10.1109/MCI.2009.934561

G. Acampora, M. Gaeta, and V. Loia, Exploring e-Learning Knowledge Through Ontological Memetic Agents, IEEE Computational Intelligence Magazine, vol.5, issue.2, pp.66-77, 2010.
DOI : 10.1109/MCI.2010.936306

URL : http://repository.tue.nl/755840