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Susan L. EpsteinThe CUNY Graduate School, Department
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HoyleHoyle
is a FORR-based program that learns to play many
different board games well. Its premise is that agreement among varying
heuristic viewpoints is a valid decision-making principle. Hoyle minimizes
search, focusing instead upon reasonable rationales and multiple learning
methods. Hoyle learns during competition, and demonstrates substantial,
learned expertise after relatively little training. Work with Hoyle
has pioneered the ability to learn heuristic Advisors in FORR. Hoyle
was the first program that learned to play more than one game. Key
references Lock, E. and Epstein, S. L. 2004. Learning and Applying Competitive
Strategies. In Proceedings of AAAI-04.
San Jose: 354-359. Epstein, S. L.
2001. Learning to Play Expertly: A Tutorial on Hoyle. Machines That Learn
to Play Games. J. F_rnkranz and M. Kubat. Huntington, NY, Nova Science:
153-178. Epstein, S.L., J. Gelfand, and
E.T. Loc. 1998, Learning Game-Specific Spatially-Oriented Heuristics. Constraints. 3(2-3): p. 239-253. Additional
references Epstein, S.L. 2000. Building a Worthy Opponent. In Proceedings of AAAI
Fall Symposium on Human Agent Simulation. MA: AAAI. Epstein, S. L. 1999. Game Playing: The Next Moves. In Proceedings of the
Sixteenth National Conference on Artificial Intelligence. Orlando, FL:
987-993. Epstein, S. L., Gelfand, J. and Lock, E. (1998). Learning How to
Satisfice. In Proceedings of the AAAI Spring Symposium on Satisficing. Palo
Alto, CA: AAAI. Gelfand, J. J., Epstein, S. L. and Powell, W. B. 1998. Integrating
Pattern-Based Reasoning in Multimodal Decision Systems. In Proceedings of the
AAAI Spring Symposium on Multimodal Reasoning. Palo Alto, CA: AAAI. Sand, S.B., Ziskind, E., Gelfand, J.J., and Epstein, S.L. 1998. Relating
Perceptual and Functional Features in Game Playing. In Proceedings of the
Twentieth Annual Meeting of the Cognitive Science Society. Epstein, S. L. and Shih, J. 1997. Learning from Sequential Examples:
Initial Results with Instance-Based Learning. In Proceedings of the MLNet
Workshop on Case-Based Learning: Beyond Classification of Feature Vectors,
Prague: ECML-97. Epstein, S. L. and Gelfand, J. 1996. The Creation of New Problem-Solving
Agents from Experience with Visual Features. In Proceedings of the AAAI Workshop
on Computational Cognitive Modeling: Source of the Power, Portland, OR: AAAI.
Epstein, S. L. and Gelfand, J. 1996. Spatially-Oriented Agents Improve a
Multi-Agent Decision-Making Program. In Proceedings of the AAAI Workshop on
Spatial and Temporal Reasoning, Portland, OR: AAAI. Epstein, S. L. 1995. Learning in the Right Places. Journal of the Learning
Sciences, 4 (3): 281-319. Epstein, S. L. 1995. On the Roles of Search and Learning in Time-Limited
Decision Making. In Proceedings of the Seventeenth Annual Cognitive Science
Conference, 568-573. Pittsburgh: Lawrence Earlbaum Associates. Epstein, S. L. and Gelfand, J. 1995. Learning New Spatially-Oriented
Game-Playing Agents through Experience. In Proceedings of the Seventeenth
Annual Cognitive Science Conference, 562-567. Pittsburgh: Lawrence Earlbaum
Associates. Epstein, S. L. 1995. Collaboration and Interdependence in Limitedly
Rational Agents. In Proceedings of the AAAI Fall Symposium on Rational
Agency, Cambridge, MA: AAAI. Epstein, S. L. 1994. Toward an Ideal Trainer.
Machine Learning, 15 (3): 251-277. Epstein, S. L. 1994. Hard Questions about Easy Tasks - Issues from
Learning to Play Games. In S. J. Hanson, G. A. Drastal, & R. L. Rivest
(Ed.), Computational Learning Theory and Natural Learning Systems, Volume 1:
Constraints and Prospects (pp. 487-521). Cambridge, MA: MIT Press. Epstein, S. L. 1994. Identifying the Right Reasons: Learning to Filter
Decision Makers. In Proceedings of the AAAI 1994 Fall Symposium on Relevance,
68-71. New Orleans: AAAI. Epstein, S. L. and Levinson, R. 1994. AAAI93 Fall Symposium Reports -
Games: Planning and Learning. AI Magazine 15 (1): 14-15. Epstein, S. L. 1993. Toward a Theory of Well-Guided Search. In Games:
Planning and Learning - Papers from the 1993 AAAI Fall Symposium, 115-122.
Menlo Park, CA: AAAI Press. Epstein, S. L., Gelfand, J., Abadie, P., Lesniak, J. and Midgley, F. 1993.
Thinking and Seeing in Game Playing: Integrating Pattern Recognition and
Symbolic Learning. In Proceedings of the Second International Workshop on
Multistrategy Learning, 301-308. West Virginia: Epstein, S. L., Gelfand, J., Lesniak, J. and Abadie, P. 1993. The
Integration of Visual Cues into a Multiple-Advisor Game-Learning Program. In
Games: Planning and Learning - Papers from the 1993 AAAI Fall Symposium,
92-100. Menlo Park, CA: AAAI Press. Epstein, S. L. 1992. Learning Expertise from the Opposition - The Role of
the Trainer in a Competitive Environment. In Proceedings of the Ninth
Canadian Conference on Artificial Intelligence, 236-243. Vancouver: Morgan
Kaufman. Epstein, S. L. 1992. Memory and Concepts in Reactive Learning. In
Proceedings of the Canadian Workshop on Machine Learning. Epstein, S. L. 1991. Deep Forks in Strategic Maps - Playing to Win. In D.
N. L. Levy, & D. F. Beal (Ed.), Heuristic Programming in Artificial
Intelligence 2 - The Second Computer Olympiad (pp. 189-203). Chichester:
Ellis Horwood Limited. Epstein, S. L. 1991. Learning to Play Two-Person Games. In F. Geyer (Ed.),
The Cybernetics of Complex Systems: Self-Organization, Evolution, and Social
Change (pp. 149-162). USA: Intersystems Publications. Epstein, S. L. 1990. Learning Plans for Competitive Domains. In
Proceedings of the Seventh International Conference on Machine Learning,
190-197. Austin: Morgan Kaufmann. Epstein, S. L. 1990. Learning to Control a Blackboard System for Game
Playing. In Proceedings of the AAAI Workshop on Blackboard Systems, Boston,
MA: Epstein, S. L. 1989. The Intelligent Novice - Learning to Play Better. In
D. N. L. Levy, & D. F. Beal (Ed.), Heuristic Programming in Artificial
Intelligence - The First Computer Olympiad. New York: Ellis Horwood. Epstein, S. L. 1989. Mediation among Advisors. In Proceedings of the AAAI
Symposium on AI and Limited Rationality, 35-39. Stanford University: Edmund
Hoyle was an 18th century English chess player who codified the rules
for all the popular board games and card games he knew. "According
to Hoyle" means "playing by the rules." This
material is based upon work supported by the National Science Foundation
under Grant Nos. 9423085, #IRI-9703475, 9222720, and #9001936, by the
New York State Technological Development Graduate Research and Technology
Initiative, and by the PSC-CUNY Research Foundation. Any
opinions, findings, and conclusions or recommendations expressed in
this material are those of the author(s) and do not necessarily reflect
the views of the National Science Foundation, New York State, or PSC-CUNY. [top of the page] |
