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Computer Science
695 Park Ave.
NY, NY 10021

 

Susan L. Epstein

The CUNY Graduate School, Department of Computer Science and

 Hunter College, Department of Computer Science

 

 

 

 

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Hoyle

Hoyle 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.

Epstein, S. L., Gelfand, J. and Lesniak, J. 1996. Pattern-Based Learning and Spatially-Oriented Concept Formation with a Multi-Agent, Decision-Making Expert. Computational Intelligence, 12 (1): 199-221.

Epstein, S. L. 1992. Prior Knowledge Strengthens Learning to Control Search in Weak Theory Domains. International Journal of Intelligent Systems, 7: 547-586.

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. 

Epstein, S. L. and Shih, J. (1998). Sequential Instance-Based Learning. In Proceedings of AI-98. Vancouver.

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., Gelfand, J. and Lesniak, J. 1996. Pattern-Based Learning and Spatially-Oriented Concept Formation with a Multi-Agent, Decision-Making Expert. Computational Intelligence, 12 (1): 199-221.

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. and Gelfand, J. 1995. Learning Spatial Concepts through Experience. In Proceedings of the IJCAI Workshop on Spatial and Temporal Reasoning, 47-56. Montreal: 

Ratterman, M. J. and Epstein, S. L. 1995. Skilled like a Person: A Comparison of Human and Computer Game Playing. In Proceedings of the Seventeenth Annual Conference of the Cognitive Science Society, 709-714. Pittsburgh: Lawrence Erlbaum 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. For the Right Reasons: The FORR Architecture for Learning in a Skill Domain. Cognitive Science, 18 (3): 479-511.

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.

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