A strategic metagame player for general chess-like games

Computational Intelligence

Volumn 12, Issue 1, 1996, Pages 177-198

  Pell, Barney ^a  

^a NASA AMES RESEARCH CENTER   (United States)

Author keywords

Chess; Evaluation function learning; Game generation; Games; Heuristic search; Knowledge representation; Metagame; Methodology; Rule analysis; Strategy

Indexed keywords

FUNCTION EVALUATION; HEURISTIC METHODS; KNOWLEDGE REPRESENTATION; LEARNING SYSTEMS; PROBLEM SOLVING;

GAME GENERATION; HEURISTIC SEARCH; METAGAME PLAYER;

GAME THEORY;

EID: 0030085010     PISSN: 08247935     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.1467-8640.1996.tb00258.x     Document Type: Article

References (47)

1. ABRAMSON, B. 1990. Expected-outcome: a general model of static evaluation. IEEE Transactions on Pattern Analysis and Machine Intelligence 12(2).
2. ANGELINE, P., and J. POLLACK. 1993. Competitive environments evolve better solutions for complex tasks. In Proceedings of the Fifth International Conference on Genetic Algorithms. Edited by S. Forrest. Morgan Kaufmann.
3. BAUM, E. B., and W. D. SMITH. 1993. Best play for imperfect players and game tree search. In Proceedings of the AAAI Fall Symposium on Games: Planning and Learning. AAAI Press.
4. BERLINER, H. 1974. Chess as problem solving: The developments of a tactics analyzer. Ph.D. dissertation, Computer Science Department, Carnegie-Mellon University, Pittsburgh, PA.
5. BOTVINNIK, M. M. 1970. Computers, chess and long-range planning. Springer-Verlag, New York.
6. BRAMER, M. A., Editor. 1983. Computer game-playing: theory and practice. Ellis-Horwood Publishers.
7. CALLAN, J. P. 1993. Knowledge-based feature generation for inductive learning. Ph.D. dissertation, Department of Computer and Information Science, University of Massachusetts, Amherst, MA.
8. CALLAN, J. P., T. E. FAWCETT, and E. L. RISSLAND. 1991. Adaptive case-based reasoning. In IJCAI-91.
9. CALLAN, J. P., and P. UTGOFF. 1991. Constructive induction on domain knowledge. In Proceedings of the Ninth National Conference on Artificial Intelligence (AAAI-91), pp. 614-619.
10. CHURCH, R. M., and K. W. CHURCH. 1979. Plans, goals, and search strategies for the selection of a move in chess. In Chess skill in man and machine. Edited by P. W. Frey. Springer-Verlag.
11. COLLINS, G., L. BIRNBAUM, B. KRULWICH, and M. FREED. 1991. Plan debugging in an intentional system. In IJCAI-91.
12. DE GREY, A. 1985. Towards a versatile self-learning board game program. Final project, Tripos in Computer Science, University of Cambridge.
13. ELLMAN, T. 1988. Approximate theory formation: an explanation-based approach. In Proceedings of the Sixth National Conference on Artificial Intelligence (AAAI-88). AAAI, Cambridge, MA, pp. 570-574.
14. EPSTEIN, S. 1989. The intelligent novice - learning to play better. In Heuristic programming in artificial intelligence - the first computer olympiad. Edited by D. Levy and D. Beal. Ellis Horwood.
15. EPSTEIN, S. 1994. Toward an ideal trainer. Machine Learning 15(3).
16. FAWCETT, T. E., and P. E. UTGOFF. 1992. Automatic feature generation for problem solving systems. In Proceedings of the Ninth International Workshop on Machine Learning. Edited by D. Sleeman and P. Edwards. Aberdeen, Scotland.
17. FINDLER, N. V., G. L. SICHERMAN, and B. MCCALL. 1983. A multi-strategy gaming environment. In Computer game-playing. Edited by M. A. Bramer. Ellis-Horwood Publishers, chap. 17.
18. FLANN, N. S., and T. G. DIETTERICH. 1989. A study of explanation-based methods for inductive learning. Machine Learning 4(2):187-226.
19. FRANK, I., D. BASIN, and A. BUNDY. 1992. An adaptation of proof-planning to declarer play in bridge. In Proceedings of the European Conference on Artificial Intelligence, 72-76. Longer version available from Edinburgh as DAI Research Paper No. 575.
20. GAMBÄCK, B., M. RAYNER, and B. PELL. 1991. An architecture for a sophisticated mechanical bridge player. In Heuristic programming in artificial intelligence 2 - the second computer olympiad. Edited by D. Levy and D. Beal. Ellis-Horwood.
21. GAMBÄCK, B., M. RAYNER, and B. PELL. 1993. Pragmatic reasoning in bridge. Technical Report No. 299, University of Cambridge Computer Laboratory.
22. GHERRITY, M. 1993. A game-learning machine. Ph.D. dissertation, Computer Science Department, University of California, San Diego.
23. GOOD, I. J. 1968. A five-year plan for automatic chess. In Machine intelligence 2. Edited by E. Dale and D. Michie. Oliver and Boyd, pp. 89-118.
24. Hunvald, H. 1972. Chess: Quotations from the masters. Peter Pauper Press, Mount Vernon, New York.
25. KIERULF, A., K. CHEN, and J. NIEVERGELT. 1990. Smart game board and go explorer: a case study in software and knowledge engineering. Communications of the ACM 33(2).
26. LEE, K.-F., and S. MAHAJAN. 1988. A pattern classification approach to evaluation function learning. Artificial Intelligence 36(1):1-25.
27. LEVINSON, R. A., and R. SNYDER. 1991. Adaptive, pattern-oriented chess. In Proceedings of the Ninth National Conference on Artificial Intelligence (AAAI-91) (1991), pp. 601-605.
28. LEVINSON, R. A., and R. SNYDER. 1993. Distance: towards the unification of chess knowledge. International Computer Chess Association Journal 16(3):123-136.
29. LEVY, D., and M. NEWBORN. 1991. How computers play chess. W.H. Freeman and Company, New York.
30. MOSTOW, J. 1983. A problem-solver for making advice operational. In Proceedings of the National Conference on Artificial Intelligence (AAAI-83). AAAI, Cambridge, Mass. pp. 279-283.
31. NILSSON, N. J. 1980. Principles of artificial intelligence. Tioga Publishing Co., Palo Alto, CA.
32. PELL, B. 1992a. Metagame: a new challenge for games and learning. In Heuristic programming in artificial intelligence 3 - the third computer olympiad. Edited by H. van den Herik and L. Allis. Ellis-Horwood. Also appears as University of Cambridge Computer Laboratory Technical Report No. 276.
33. PELL, B. 1992b. Metagame in symmetric, chess-like games. In Heuristic programming in artificial intelligence 3 - the third computer olympiad. Edited by H. van den Herik and L. Allis. Ellis-Horwood. Also appears as University of Cambridge Computer Laboratory Technical Report No. 277.
34. PELL, B. 1993a. Logic programming for general game playing. In Proceedings of ML93 Workshop on Knowledge Compilation and Speedup Learning. Machine Learning Conference, Amherst, MA. Also appears as University of Cambridge Computer Laboratory Technical Report No. 302.
35. PELL, B. 1993b. Strategy generation and evaluation for meta-game playing. Ph.D. dissertation, Computer Laboratory, University of Cambridge. Also appears as University of Cambridge Computer Laboratory Technical Report No. 315.
36. RUSSELL, S., and E. WEFALD. 1992. Do the right thing. MIT Press, Cambridge, MA.
37. SAMUELS, A. L. 1967. Some studies in machine learning using the game of Checkers. II. IBM Journal 11:601-617.
38. SCHAEFFER, J., J. CULBERSON, N. TRELOAR, B. KNIGHT, P. LU, and D. SZAFRON. 1991. Reviving the game of checkers. In Heuristic programming in artificial intelligence 2 - the second computer olympiad. Edited by D. Levy and D. Beal. Ellis Horwood.
39. SCHRAUDOLPH, N. N., P. DAYAN, and T. J. SEJNOWSKI. 1994. Temporal difference learning of position evaluation in the game of go. In Advances in Neural Information Processing 6. Edited by J. Cowan, G. Tesauro, and J. Alspector. Morgan Kaufmann, San Francisco, CA.
40. SMITH, S. J., and D. S. NAU. 1993. Strategic planning for imperfect-information games. In Proceedings of the AAAI Fall Symposium on Games: Planning and Learning, 84-91. AAAI Press.
41. SUTTON, R. S. 1984. Temporal credit assignment in reinforcement learning. Ph.D. dissertation, Department of Computer and Information Science, University of Massachusetts, Amherst, MA.
42. TADEPALLI, P. 1989. Lazy explanation-based learning: a solution to the intractable theory problem. In Proceedings of the Eleventh International Joint Conference on Artificial Intelligence. IJCAL, Los Altos, CA. pp. 694-700.
43. TESAURO, G. 1994. TD-Gammon, A self-teaching backgammon program achieves master-level play. Neural Computation 6(2):215-219.
44. TUNSTALL-PEDOE, W. 1991. Genetic algorithms optimizing evaluation functions. Journal ICCA 14(3):119-128.
45. WELLMAN, M. P., and J. DOYLE. 1991. Preferential semantics for goals. In Proceedings of the Ninth National Conference on Artificial Intelligence (AAAI-91) pp. 698-703.
46. WILKINS, D. E. 1982. Using knowledge to control tree search. Artificial Intelligence 18:1-51.
47. WILLIAMS, T. G. 1972. Some studies in game playing with a digital computer. In Representation and meaning. Edited by L. Siklossy and H. Simon. Prentice-Hall.