Expected-outcome: a general model of static evaluation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.12, issue.2, pp.182-193, 1990. ,
DOI : 10.1109/34.44404
Searching for Solutions in Games and Artificial Intelligence, 1994. ,
A simulated annealing algorithm with constant temperature for discrete stochastic optimization, Management Science, vol.45, issue.5, pp.748-764, 1999. ,
A Bayesian approach to relevance in game playing, Artificial Intelligence, vol.97, issue.1-2, pp.195-242, 1997. ,
DOI : 10.1016/S0004-3702(97)00059-3
Using selective-sampling simulations in poker, Proceedings of the AAAI Spring Symposium on Search Techniques for Problem Solving under Uncertainty and Incomplete Information, 1999. ,
Associating Shallow and Selective Global Tree Search with Monte Carlo for 9 ?? 9 Go, Fourth International Conference on Computers and Games, 2004. ,
DOI : 10.1007/11674399_5
Move-Pruning Techniques for Monte-Carlo Go, Advances in Computer Games 11, 2005. ,
DOI : 10.1007/11922155_8
Computer Go: An AI oriented survey, Artificial Intelligence, vol.132, issue.1, pp.39-103, 2001. ,
DOI : 10.1016/S0004-3702(01)00127-8
Monte-Carlo Go Developments, Proceedings of the 10th Advances in Computer Games Conference, 2003. ,
DOI : 10.1007/978-0-387-35706-5_11
Combining tactical search and Monte- Carlo in the game of go, Proceedings of the IEEE Symposium on Computational Intelligence and Games, 2005. ,
An Adaptive Sampling Algorithm for Solving Markov Decision Processes, Operations Research, vol.53, issue.1, pp.126-139, 2005. ,
DOI : 10.1287/opre.1040.0145
Simulation budget allocation for further enhancing the efficiency of ordinal optimization, Discrete Event Dynamic Systems, vol.10, issue.3, pp.251-270, 2000. ,
DOI : 10.1023/A:1008349927281
Monte-Carlo planning in RTS games, Proceedings of the IEEE Symposium on Computational Intelligence and Games, 2005. ,
Evaluation in Go by a Neural Network Using Soft Segmentation, Proceedings of the 10th Advances in Computer Games Conference, 2003. ,
DOI : 10.1007/978-0-387-35706-5_7
Optimal allocation of simulation experiments in discrete stochastic optimization and approximative algorithms, European Journal of Operational Research, vol.101, issue.2, pp.245-260, 1997. ,
DOI : 10.1016/S0377-2217(96)00396-7
GIB: Steps toward an expert-level bridge-playing program, Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, pp.584-593, 1999. ,
Methods for Statistical Inference: Extending the Evolutionary Computation Paradigm, 1999. ,
A sparse sampling algorithm for near-optimal planning in large Markov decision processes, Proceedings of the Sixteenth Internation Joint Conference on Artificial Intelligence, pp.1324-1331, 1999. ,
An analysis of alpha-beta pruning, Artificial Intelligence, vol.6, pp.293-326, 1975. ,
Searching with Probabilities, 1984. ,
On-line search for solving large Markov decision processes, Proceedings of the 16th European Conference on Artificial Intelligence, 2004. ,
Efficient Control of Selective Simulations, ICGA Journal, vol.27, issue.2, pp.67-79, 2004. ,
DOI : 10.1007/11674399_1
Learning to predict by the methods of temporal differences, Machine Learning, pp.9-44, 1988. ,
DOI : 10.1007/BF00115009
Reinforcement Learning: An Introduction, 1998. ,
Programming backgammon using self-teaching neural nets, Artificial Intelligence, vol.134, issue.1-2, pp.181-199, 2002. ,
DOI : 10.1016/S0004-3702(01)00110-2
Combinatorics of Go, Proceedings of the Fifth International Conference on Computer and Games, 2006. ,
DOI : 10.1007/978-3-540-75538-8_8
Computer Go tournaments on KGS, 2005. ,