Learning to bid in bridge

Machine Learning

Volumn 63, Issue 3, 2006, Pages 287-327

  Amit, Asaf ^a   Markovitch, Shaul ^a  

^a TECHNION ISRAEL INSTITUTE OF TECHNOLOGY   (Israel)

Author keywords

Bridge; Learning to cooperate; Opponent modeling; Partner modeling

Indexed keywords

ALGORITHMS; ANIMATION; COMPUTER SYSTEMS PROGRAMMING; DECISION MAKING; MONTE CARLO METHODS; OBSERVABILITY;

BRIDGE; LEARNING TO COOPERATE; OPPONENT MODELING; PARTNER MODELING;

LEARNING SYSTEMS;

EID: 33744825172     PISSN: 08856125     EISSN: 15730565     Source Type: Journal    
DOI: 10.1007/s10994-006-6225-2     Document Type: Article

References (53)

1. Ando, T., Kobayashi, N., & Uehara. T. (2003). Cooperation and competition of agents in the auction of computer bridge. Electronics and Communications in Japan, 86(12).
2. Belladonna, G., & Garozzo. B. (1975). Precision & super precision bidding. Cassell, London.
3. Billings, D., Burch, N., Davidson, A., Holte, R., Schaeffer, J., Schauenberg, T., & Szafron, D. (2003). Approximating game-theoretic optimal strategies for fullscale poker. In: Proceedings of the Eighteens International Joint Conference on Artificial Intelligence (pp. 661-668).
4. Billings, D., Davidson, A., Schaeffer, J., & Szafron, D. (2002). The challenge of poker. Artificial Intelligence 134:1-2, 201-240.
5. Billings, D., Papp, D., Schaeffer, J., & Szafron, D. (1998). Opponent modeling in poker. In: Proceedings of the Fifteenth National Conference on Artificial Intelligence, (pp. 493-499).
6. Billings, D., Pena, L., Schaeffer, J., & Szafron, D. (1998). Using probabilistic knowledge and simulation to play poker. In: Proceedings of the Sixteenth National Conference on Artificial Intelligence (pp. 697-703).
7. Bird, R., (1999). BTM's first steps into computing. Computer Resurrection: The Bulletin of the Computer Conservation Society, 22, 12-18.
8. Bruce, J., Bowling, M., Browning, B., & Veloso, M. (2002). Multi-robot team response to a multi-robot opponent team. In: Proceedings of the 2003 IEEE International Conference on Robotics and Automation (pp. 2281-2286).
9. Carley, G. (1962). A program to play contract bridge. Master's thesis, Dept. of Electrical Engineering, Massachussets Institute of Technology, Cambridge, Massachussets.
10. Carmel, D., & Markovitch, S. (1996a). Incorporating opponent models into adversary search. In: Proceedings of the Thirteenth National Conference on Artificial Intelligence (pp. 120-125). Portland, Oregon.
11. Carmel, D., & Markovitch, S. (1996b). Learning and using opponent models in adversary search. Technical Report CIS9609, Technion.
12. Carmel, D., & Markovitch, S. (1998). Model-based learning of interaction strategies in multi-agent systems. Journal of Experimental and Theoretical Artificial Intelligence, 10:3, 309-332.
13. Cohen, L. (2002). Larry Cohen's bidding challenge. Master Point Print, Toronto.
14. Davidson, A., Billings, D., Schaeffer, J., & Szafron, D. (2000). Improved opponent modeling in poker. In: Proceedings of the 2000 International Conference on Artificial Intelligence (pp. 1467-1473).
15. Donkers, H. (2003). Nosce Hostem - Searching with opponent models. Ph.D. thesis, Universiteit Maastricht.
16. Donkers, H., Uiterwijk, J., & van, den Herik, H. (2001). Probabilistic opponent-model search. Information Sciences, 135:3-4, 123-149.
17. Eskes, O. (1998). The par contest. Imp Magazine, 9 (7).
18. Feigenbaum, E., & Simon, H. (1984). EPAM-like models of recognition and learning. Cognitive Science, 8:43, 305-336.
19. Finkelstein, L., & Markovitch, S. (1998). Learning to play chess selectively by acquiring move patterns. ICCA Journal, 21:2, 100-119.
20. Frank, I. (1998). Search and planning under incomplete information: study using bridge card play. Springer.
21. Gambäck, B., Rayner, M., & Pell, B. (1993). Pragmatic reasoning in bridge. Technical Report CRC-030, SRI International Cambridge Computer Science Reasearch Center.
22. Gao, X. Iida, H. Uiterwijk, J., & van den Herik. H. J. (1999). A speculative strategy. Lecture Notes in Computer Science, 1558, 74-92.
23. Ginsberg, M. L. (2001). GIB: Imperfect information in a computationally challenging game. Journal of Artificial Intelligence Research, 14, 303-358.
24. Goldman, B. (1978). Aces scientific. Max Hardy.
25. Hyatt, R. M. (1999). Book learning - A methodology to tune an opening book automatically. International Computer Chess Association Journal, 22:1, 3-12.
26. Iida, H., Uiterwijk, J. W., & van den Herik, H. (2000). Cooperative strategies for pair playing. In: H. van den Herik and H. Iida (eds.), Games in AI Research. Universiteit Maastricht (pp. 189-201).
27. Iida, H., Uiterwijk, J. W. H., van den Herik, H. J., & Herschberg, I. S., (1993). Potential applications of opponent-model search, Part I: The domain of applicability. ICCA Journal, 16:4, 201-208.
28. Iida, H., Uiterwijk, J. W. H., van den Herik, H. J., & Herschberg, I. S. (1994). Potential applications of opponent-model search, Part II: risks and strategies. ICCA Journal, 17:1, 10-14.
29. Jamroga, W. (1999). Modelling artificial intelligence on a case of bridge card play bidding. In: Proceedings of the 8th International Workshop on Intelligent Information Systems (pp. 267-277) Ustron, Poland.
30. Jamroga, W. (2001). A defense model for games with incomplete information. Lecture Notes in Computer Science, 2174, 260-274.
31. Jansen, P. J. (1992). Using knowledge about the opponent in game-tree search. Ph.D. thesis, Carnegie Mellon University.
32. Klinger, R. (2001). Modern losing trick count. Orion.
33. Levy, D. (1989). The million pound bridge program. In: D. Levy and D. Beal (eds.), Heuristic programming in artificial intelligence - First Computer Olympiad (pp. 93-105).
34. Lindelöf, E. (1983). COBRA - The computer-designed bidding system. England: Victor Gollancz.
35. Luckhardt, C. A., & Irani, K. B. (1986). An algorithmic solution of N-person games. In: Proceedings of the Ninth National Conference on Artificial Intelligence (pp. 158-162). Philadelfia, PA.
36. Lustrek, M., Gams, M., & Bratko, I. (2003). A program for playing tarok. ICGA Journal, 26:3, 190-197.
37. Macleod, J. (1989). Microbridge - A Computer Developed Approach to Bidding. In: D. Levy and D. Beal (eds.), Heuristic programming in artificial intelligence - the first computer olympiad (pp. 81-87).
38. Mahmood, Z. (1994). Bridge my way. Natco Press.
39. Markovitch, S., & Reger, R. (2005). Learning and exploiting relative weaknesses of opponent agents. Autonomous Agents and Multi-agent Systems, 10:2, 103-130.
40. Markovitch, S., & Sella, Y. (1996). Learning of resource allocation strategies for game playing. Computational Intelligence, 12:1, 88-105.
41. Samuel, A. L. (1959). Some studies in machine learning using the game of checkers. IBM Journal of Research and Development, 3:3, 211-229.
42. Schaeffer, J. (2000). The games computers (and People) play. In: Marvin Zelkowitz (ed.), Advances in computer 50, (pp. 189-266). Academic Press.
43. Scott, P. D., & Markovitch, S. (1991). Representation generation in an exploratory learning system. In: D. Fisher and M. Pazzani (eds.), Concept formation: Knowledge and experience in unsupervised learning. Morgan Kaufmann.
44. Scott, P. D., & Markovitch, S. (1993). Experience selection and problem choice in an exploratory learning system. Machine Learning, 12, 49-67.
45. Sen, S., & Arora, N. (1997). Learning to take risks. In: AAA1-97 Workshop on Multiagent Learning. (pp. 59-64).
46. Sen, S., & Sekaran, M. (1998). Individual learning of coordination knowledge. Journal of Experimental & Theoretical Artificial Intelligence 10:3, (p. 333-356).
47. Shi, J., & Littman, M. (2001). Abstraction models for game theoretic poker. Computers and Games, (pp. 333-345).
48. Smith, S. J. J., Nau, D., & Throop, T. (1996). A planning approach to declarer play in contract bridge. Computational Intelligence, 12:1, 106-130.
49. Smith, S. J. J., Nau, D., & Throop, T. (1998a). Computer bridge: A big win for AI planning. AI Magazine, 2.-19, 93-105.
50. Smith, S. J. J., Nau, D., & Throop, T. (1998b). Success in spades: Using AI planning techniques to win the world championship of computer bridge. In: Proceedings of the Fifteenth National Conference on Artificial Intelligence, (pp. 1079-1086).
51. Stanier, A. M. (1975). BRIBIP: A bridge bidding program. In: The Proceedings of the Fourth International Joint Conference on Artificial Intelligence (pp. 374-378).
52. Sturtevant, N. (2004). Current challenges in multi-player game search. In: Proceedings of Computers and Games. Israel.
53. Wasserman, A. (1970). Realization of a skillful bridge bidding program. Fall Joint Computer Conference, (pp. 433-444). Houston, Texas.