Grid coevolution for adaptive simulations: Application to the building of opening books in the game of go

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5484 LNCS, Issue , 2009, Pages 323-332

  Audouard, Pierre ^a   Chaslot, Guillaume ^b   Hoock, Jean Baptiste ^c   Perez, Julien ^c   Rimmel, Arpad ^c   Teytaud, Olivier ^c  

^a Go Expert ^*

^b MAASTRICHT UNIVERSITY   (Netherlands)

^c CNRS   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE SIMULATION; CO-EVOLUTION; MARKOV DECISION PROCESS;

COMPUTER SCIENCE; MARKOV PROCESSES;

GAME THEORY;

EID: 67650699537     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-01129-0_36     Document Type: Conference Paper

References (15)

1. Buro, M.: Toward opening book learning. ICCA Journal 22, 98-102 (1999)
2. Chaslot, G., Winands, M., Uiterwijk, J., van den Herik, H., Bouzy, B.: Progressive strategies for monte-carlo tree search. In: Wang, P., et al. (eds.) Proceedings of the 10th Joint Conference on Information Sciences (JCIS 2007), pp. 655-661. World Scientific Publishing Co. Pte. Ltd., Singapore (2007)
3. Collet, P., Lutton, E., Raynal, F., Schoenauer, M.: Polar ifs + parisian gp = efficient inverse ifs problem solving. Genetic Programming and Evolvable Machines 1(4), 339-361 (2000)
4. Coulom, R.: Efficient selectivity and backup operators in monte-carlo tree search. In: Ciancarini, P., van den Herik, H.J. (eds.) Proceedings of the 5th International Conference on Computers and Games, Turin, Italy (2006)
5. Donninger, C., Lorenz, U.: Innovative opening-book handling. In: van den Herik, H.J., Hsu, S.-C., Hsu, T.-s., Donkers, H.H.L.M.(eds.) CG 2005. LNCS, vol.4250, pp. 1-10. Springer, Heidelberg (2006)
6. Drake, P., Chen, Y.-P.: Coevolving partial strategies for the game of go. In: International Conference on Genetic and Evolutionary Methods. CSREA Press (2008)
7. Gelly, S., Silver, D.: Combining online and offline knowledge in uct. In: ICML 2007: Proceedings of the 24th international conference on Machine learning, pp. 273-280. ACM Press, New York (2007) (Pubitemid 47275075)
8. Kocsis, L., Szepesvari, C.: Bandit based monte-carlo planning. In: Fürnkranz, J., Scheffer, T., Spiliopoulou, M. (eds.) ECML 2006. LNCS, vol.4212, pp. 282-293. Springer, Heidelberg (2006) (Pubitemid 44618839)
9. Müller, M.: Computer go. Artificial Intelligence 134(1-2), 145-179 (2002) (Pubitemid 34086582)
10. Nagashima, J., Hashimoto, T., Iida, H.: Self-playing-based opening book tuning. New Mathematics and Natural Computation (NMNC) 2(02), 183-194 (2006)
11. Ong, C., Quek, H., Tan, K., Tay, A.: Discovering chinese chess strategies through coevolutionary approaches. In: IEEE Symposium on Computational Intelligence and Games, pp. 360-367 (2007) (Pubitemid 47431326)
12. Péret, L., Garcia, F.: On-line search for solving markov decision processes via heuristic sampling. In: de Ḿantaras, R.L., Saitta, L. (eds.) ECAI, pp. 530-534. IOS Press, Amsterdam (2004)
13. Teytaud, O., Fournier, H.: Lower bounds for evolution strategies using vc-dimensio n. In G. Rudolph, T. Jansen, S. M. Lucas, C. Poloni, and N. Beume, editors, PPSN. In: Rudolph, G., Jansen, T., Lucas, S., Poloni, C., Beume, N. (eds.) PPSN 2008. LNCS, vol.5199, pp. 102-111. Springer, Heidelberg (2008)
14. Tromp, J., Farnebäck, G.: Combinatorics of go. In: Proceedings of 5th International Conference on Computer and Games, Torino, Italy (May 2006)
15. Wang, Y., Gelly, S.: Modifications of UCT and sequence-like simulations for Monte- Carlo Go. In: IEEE Symposium on Computational Intelligence and Games, Honolulu, Hawaii, pp. 175-182 (2007) (Pubitemid 47431300)