A Monte-Carlo approach for ghost avoidance in the Ms. Pac-Man game

2nd International IEEE Consumer Electronic Society Games Innovation Conference, ICE-GIC 2010

Volumn , Issue , 2010, Pages

  Tong, Bruce K B ^a   Sung, Chi Wan ^a  

^a CITY UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

Competition; Computational intelligence; Game; Monte Carlo simulation; Ms. Pac Man

Indexed keywords

COMPUTATIONAL INTELLIGENCE; GAME; HUMAN PLAYERS; LOOK-AHEAD; MONTE CARLO; MONTE-CARLO SIMULATION; MS. PAC-MAN; THREE STAGES;

ARTIFICIAL INTELLIGENCE; COMPETITION; INTERCALATION;

INTELLIGENT AGENTS;

EID: 79952853582     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICEGIC.2010.5716879     Document Type: Conference Paper

References (25)

1. S. M. Lucas, "Ms. Pac-Man competition," SIGEVOlution, vol. 2, no. 4, pp. 37-38, 2007.
2. J. Togelius, S. Karakovskiy and R. Baumgarten, "The 2009 Mario AI Competition," IEEE Congress on Evolutionary Computation, pp. 1-8, 2010
3. D. Loiacono, J. Togelius, P. L. Lanzi, L. Kinnaird-Heether, S. M. Lucas, M. Simmerson, D. Perez, R. G. Reynolds, Y. Saez "The WCCI 2008 Simulated Car Racing Competition," IEEE Symposium on Computational Intelligence and Games, pp. 119-126, 2008
4. J. R. Koza, Genetic Programming: on the Programing of Computers by Means of Natural Selection. MIT Press, 1992.
5. J. P. Rosca, "Generality versus size in genetic programming." Proceedings of the Genetic Programming 1996 Conference, pp. 381-387, MIT Press, 1996.
6. Szita and A. Lorincz, "Learning to play using low-complexity rule-based policies: illustrations through Ms. Pac-Man," Journal of Artificial Intelligence Research, vol. 30, no. 1, pp. 659-684, 2007.
7. J. S. D. Bonet and C. P. Stauffer, "Learning to play Pac-Man using incremental reinforcement learning," Proceedings of the Congress on Evolutionary Computation, 1999.
8. M. Gallagher and A. Ryan, "Learning to play Pac-Man: an evolutionary, rule-based approach," The 2003 Congress on Evolutionary Computation, vol. 4, pp. 2462-2469, 2003.
9. M. Gallagher and M. Ledwich, "Evolving Pac-Man players: Can we learn from raw input?," IEEE Symposium on Computational Intelligence and Games, pp. 282-287, 2007.
10. T. Thompson, L. McMillan, J. Levine and A. Andrew, "An evaluation of the benefits of look-ahead in Pac-Man," IEEE Symposium on Computational Intelligence and Games, pp. 310-315, 2008.
11. S. M. Lucas, "Evolving a neural network location evaluator to play Ms. Pac-Man," IEEE Symposium on Computational Intelligence and Games, pp. 203-210, 2005.
12. N. Wirth and M. Gallagher, "An influence map model for playing Ms. Pac-Man," IEEE Symposium on Computational Intelligence and Games, pp. 228-233, 2008.
13. H. Handa and M. Isozaki, "Evolutionary fuzzy systems for generating better Ms. Pac-Man players," IEEE International Conference on Fuzzy Systems, pp. 2182-2185, 2008.
14. H. Handa, "Constitution of Ms. Pac-Man player with critical-situation learning mechanism," Fourth International Workshop on Computational Intelligence & Applications, pp. 48-53, 2008
15. A. Fitzgerald, P. Kemeraitis and C. B. Congdon, "RAMP: A rule-based agent for Ms. Pac-Man," IEEE Congress on Evolutionary Computation, pp. 2646-2653, 2009.
16. P. Burrow and S. M. Lucas, "Evolution versus temporal difference learning for learning to play Ms. Pac-Man," IEEE Symposium on Computational Intelligence and Games, pp. 53-60, 2009.
17. L. DeLooze and W. Viner, "Fuzzy Q-Learning in a Nondeterministic Environment: Developing an Intelligent Ms. Pac-Man Agent," IEEE Symposium on Computational Intelligence and Games, pp. 162-169, 2009.
18. D. Robles, S. M. Lucas, "A simple tree search method for playing Ms. Pac-Man," IEEE Symposium on Computational Intelligence and Games, pp. 249-255, 2009.
19. R. Thawonmas and H. Matsumoto, "Automatic controller of Ms. Pac-Man and its performance: Winner of the IEEE CEC 2009 software agent Ms. Pac-Man competition," Proc. of Asia Simulation Conference 2009 (JSST 2009), 2009.
20. H. Matsumoto, T. Ashida, Y. Ozasa, T. Maruyama and R. Thawonmas, "ICE Pambush 3," Controller description paper, http://cswww.essex.ac. uk/staff/sml/pacman/cig2009/ICEPambush3/ICE%20Pambush%203.pdf (accessed 25/10/2010)
21. A. L. Samuel, "Some studies in machine learning using the game of Checkers," IBM Journal of Research and Development, vol. 3, issue 3, pp. 210-229, 1959.
22. H. Matsumoto, T. Ashida, Y. Ozasa, T. Maruyama and R. Thawonmas, "ICE Pambush 3," Controller source code, http://cswww.essex.ac.uk/ staff/sml/pacman/cig2009/ICEPambush3/ICE%20Pambush%203.zip (accessed 25/10/2010)
23. S. Gelly and D. Silver, "Achieving master level play in 9x9 computer go," Proceedings of AAAI, pp. 1537-1540, 2008.
24. C. S. Lee, M. H. Wang, G. Chaslot J. B. Hoock, A. Rimmel, O. Teytaud, S. R. Tsai, S. C. Hsu and T. P Hong, "The computational intelligence of MoGo revealed in Taiwan's Computer Go tournaments," vol. 1, issue 1, pp. 73-89, 2009.
25. G. V. d. Broeck, K. Driessens and J. Ramon, "Monte-Carlo Tree Search in Poker Using Expected Reward Distributions," Proceedings of the 1st Asian Conference on Machine Learning: Advances in Machine Learning, pp. 367-381, 2009