Auer, P., Cesa-Bianchi, N., Fischer, P.: Finite-Time Analysis of the Multiarmed Bandit Problem. Machine Learning 47(2-3), 235–256 (2002)
CrossRef
MATH
Google Scholar
Baier, H., Winands, M.H.M.: Monte-Carlo Tree Search and Minimax Hybrids. In: 2013 IEEE Conference on Computational Intelligence and Games, CIG 2013, pp. 129–136 (2013)
Google Scholar
Bouzy, B.: Associating Domain-Dependent Knowledge and Monte Carlo Approaches within a Go Program. Information Sciences 175(4), 247–257 (2005)
CrossRef
Google Scholar
Browne, C., Powley, E.J., Whitehouse, D., Lucas, S.M., Cowling, P.I., Rohlfshagen, P., Tavener, S., Perez, D., Samothrakis, S., Colton, S.: A Survey of Monte Carlo Tree Search Methods. IEEE Transactions on Computational Intelligence and AI in Games 4(1), 1–43 (2012)
CrossRef
Google Scholar
Chaslot, G.M.J.B., Winands, M.H.M., van den Herik, H.J., Uiterwijk, J.W.H.M., Bouzy, B.: Progressive Strategies for Monte-Carlo Tree Search. New Mathematics and Natural Computation 4(3), 343–357 (2008)
MathSciNet
CrossRef
MATH
Google Scholar
Clune, J.E.: Heuristic Evaluation Functions for General Game Playing. Ph.D. thesis, University of California, Los Angeles, USA (2008)
Google Scholar
Coulom, R.: Efficient Selectivity and Backup Operators in Monte-Carlo Tree Search. In: van den Herik, H.J., Ciancarini, P., Donkers, H.H.L.M(J.) (eds.) CG 2006. LNCS, vol. 4630, pp. 72–83. Springer, Heidelberg (2007)
CrossRef
Google Scholar
Finnsson, H., Björnsson, Y.: Game-Tree Properties and MCTS Performance. In: IJCAI 2011 Workshop on General Intelligence in Game Playing Agents (GIGA 2011), pp. 23–30 (2011)
Google Scholar
Gelly, S., Silver, D.: Combining Online and Offline Knowledge in UCT. In: Ghahramani, Z. (ed.) 24th International Conference on Machine Learning, ICML 2007. ACM International Conference Proceeding Series, vol. 227, pp. 273–280 (2007)
Google Scholar
Gelly, S., Wang, Y., Munos, R., Teytaud, O.: Modification of UCT with Patterns in Monte-Carlo Go. Tech. rep., HAL - CCSd - CNRS, France (2006)
Google Scholar
van den Herik, H.J., Xu, X., Ma, Z., Winands, M.H.M. (eds.): CG 2008. LNCS, vol. 5131. Springer, Heidelberg (2008)
MATH
Google Scholar
Knuth, D.E., Moore, R.W.: An Analysis of Alpha-Beta Pruning. Artificial Intelligence 6(4), 293–326 (1975)
MathSciNet
CrossRef
MATH
Google Scholar
Kocsis, L., Szepesvári, C.: Bandit Based Monte-Carlo Planning. In: Fürnkranz, J., Scheffer, T., Spiliopoulou, M. (eds.) ECML 2006. LNCS (LNAI), vol. 4212, pp. 282–293. Springer, Heidelberg (2006)
CrossRef
Google Scholar
Lanctot, M., Winands, M.H.M., Pepels, T., Sturtevant, N.R.: Monte Carlo Tree Search with Heuristic Evaluations using Implicit Minimax Backups. In: 2014 IEEE Conference on Computational Intelligence and Games, CIG 2014, pp. 341–348 (2014)
Google Scholar
Lorentz, R.J.: Amazons Discover Monte-Carlo. In: van den Herik (ed.) [11], pp. 13–24
Google Scholar
Lorentz, R., Horey, T.: Programming breakthrough. In: van den Herik, H.J., Iida, H., Plaat, A. (eds.) CG 2013. LNCS, vol. 8427, pp. 49–59. Springer, Heidelberg (2014)
Google Scholar
Lorentz, R.J.: Experiments with Monte-Carlo Tree Search in the Game of Havannah. ICGA Journal 34(3), 140–149 (2011)
MathSciNet
Google Scholar
Nijssen, J(P.) A.M., Winands, M.H.M.: Playout Search for Monte-Carlo Tree Search in Multi-player Games. In: van den Herik, H.J., Plaat, A. (eds.) ACG 2011. LNCS, vol. 7168, pp. 72–83. Springer, Heidelberg (2012)
CrossRef
Google Scholar
Ramanujan, R., Sabharwal, A., Selman, B.: On Adversarial Search Spaces and Sampling-Based Planning. In: Brafman, R.I., Geffner, H., Hoffmann, J., Kautz, H.A. (eds.) 20th International Conference on Automated Planning and Scheduling, ICAPS 2010, pp. 242–245. AAAI (2010)
Google Scholar
Ramanujan, R., Sabharwal, A., Selman, B.: Understanding Sampling Style Adversarial Search Methods. In: Grünwald, P., Spirtes, P. (eds.) 26th Conference on Uncertainty in Artificial Intelligence, UAI 2010, pp. 474–483 (2010)
Google Scholar
Ramanujan, R., Sabharwal, A., Selman, B.: On the Behavior of UCT in Synthetic Search Spaces. In: ICAPS 2011 Workshop on Monte-Carlo Tree Search: Theory and Applications (2011)
Google Scholar
Ramanujan, R., Selman, B.: Trade-Offs in Sampling-Based Adversarial Planning. In: Bacchus, F., Domshlak, C., Edelkamp, S., Helmert, M. (eds.) 21st International Conference on Automated Planning and Scheduling, ICAPS 2011. AAAI (2011)
Google Scholar
Sato, Y., Takahashi, D., Grimbergen, R.: A Shogi Program Based on Monte-Carlo Tree Search. ICGA Journal 33(2), 80–92 (2010)
Google Scholar
Silver, D., Tesauro, G.: Monte-Carlo Simulation Balancing. In: Danyluk, A.P., Bottou, L., Littman, M.L. (eds.) 26th Annual International Conference on Machine Learning, ICML 2009. ACM International Conference Proceeding Series, vol. 382, pp. 945–952. ACM (2009)
Google Scholar
Sturtevant, N.R.: An Analysis of UCT in Multi-Player Games. ICGA Journal 31(4), 195–208 (2008)
Google Scholar
Winands, M.H.M., Björnsson, Y., Saito, J.-T.: Monte Carlo Tree Search in Lines of Action. IEEE Transactions on Computational Intelligence and AI in Games 2(4), 239–250 (2010)
CrossRef
Google Scholar
Winands, M.H.M., Björnsson, Y.: Alpha-Beta-based Play-outs in Monte-Carlo Tree Search. In: Cho, S.-B., Lucas, S.M., Hingston, P. (eds.) 2011 IEEE Conference on Computational Intelligence and Games, CIG 2011, pp. 110–117. IEEE (2011)
Google Scholar
Winands, M.H.M., Björnsson, Y., Saito, J.T.: Monte-Carlo Tree Search Solver. In: van den Herik, et al. (eds.) [11], pp. 25–36
Google Scholar