By Topic: Way Finding and Robotics • Cognitive Science • Problem Solving, Learning, and Constraints • Natural Language Processing • Bioinformatics • Game Playing and Machine Learning • Design • Discovery in Mathematics • Education • Other topics • Thesis

Way Finding and Robotics

Zhang, Zhiao, Epstein, S.L., Breen, C., Zhu, Z., Volkmann, C. (2023) Robots in the Garden: Artificial Intelligence and Adaptive Landscapes. Journal of Digital Landscape Architecture Award 2023 for Scientific Excellence.

Epstein, S.L. 2021. Freespace Supports Metacognition for Navigation. In Proceedings of MetacogNeurIPS-2021.

R. Korpan and Epstein, S. L. (2021) Hierarchical Freespace Planning for Navigation in Unfamiliar Worlds. In Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS 2021). (Vol. 31, pp. 663-672).

R. Korpan and Epstein, S. L. (2021) Plan Explanations that Exploit a Cognitive Spatial Model. In Proceedings of the Second International Combined Workshop on Spatial Language Understanding and Grounded Communication for Robotics (ACL-IJCNLP 2021).

Epstein, S. L. and R. Korpan (2020). Metareasoning and Path Planning for Autonomous Indoor Navigation. In Proceedings of the ICAPS 2020 Workshop on Integrated Execution (IntEx) / Goal Reasoning (GR). Metareasoning and Path Planning for Autonomous Indoor Navigation. In Proceedings of the ICAPS 2020 Workshop on Integrated Execution (IntEx) / Goal Reasoning (GR).

Epstein, S. L. and R. Korpan (2019). Planning and Explanations with a Learned Spatial Model.. In Proceedings of 14th International Conference on Spatial Information Theory (COSIT 2019).

Aroor, A., S. L. Epstein and R. Korpan (2018). Online learning for crowd-sensitive planning. In Proceedings of AAMAS-2018.. Stockholm. Nominated for best robotics paper.

Korpan, R. and S. L. Epstein (2018). Toward Natural Explanations for a Robot’s Navigation Plans. In Proceedings of the Workshop on Explainable Robot Systems, HRI-2018, Chicago, IL.

Aroor, A. and S. L. Epstein (2017). Toward Crowd-Sensitive Path Planning. In Proceedings of AAAI Fall Symposium on Human-Agent Groups: Studies, Algorithms, and Challenges, Arlington, VA, AAAI.

Aroor, A., S. L. Epstein and R. Korpan (2017). MengeROS: A Crowd Simulation Tool for Autonomous Robot Navigation.. In Proceedings of AAAI Fall Symposium on Artificial Intelligence for Human-Robot Interaction, Arlington, VA, AAAI.

Korpan, R., S. L. Epstein, A. Aroor and G. Dekel (2017). WHY: Natural Explanations from a Robot Navigator. In Proceedings of AAAI Fall Symposium on Natural Communication for Human-Robot Collaboration, Arlington, VA.

Epstein, S. L. (2017). Navigation, Cognitive Spatial Models, and the Mind. In Proceedings of AAAI Fall Symposium on A Standard Model of the Mind, Arlington, VA, AAAI.

Epstein, S.L., A. Aroor, M. Evanusa, E.I. Sklar, and S. Parsons (2015). Spatial Abstraction for Autonomous Robot Navigation, In Proceedings of the VI International Conference on Spatial Cognition (ICSC). Springer: Rome.

Epstein, S.L., Aroor, A., Evanusa, M., Sklar, E.I., Simon, S. (2015) Navigation with Learned Spatial Affordances . In Proceedings of CogSci 2015. Pasadena, CA.

Epstein, S.L., Aroor, A., Evanusa, M., Sklar, E.I., Simon, S. (2015) Learning Spatial Models for Navigation, Navigation with Learned Spatial Affordances (2015). In Proceedings of CogSci 2015. Pasadena, CA.

Epstein, S.L., A. Aroor, M. Evanusa, E.I. Sklar, and S. Parsons (2015). Spatial Abstraction for Autonomous Robot Navigation. Cogniive Processing 16(1):215-219.

Ozgelen, A. T., E. Schneider, E. Sklar, M. Costantino, S. Epstein and S. Parsons (2013). A first step towards testing multiagent coordination mechanisms on mutirobot teams. In Proceedings of AAMAS Workshop on Autonomous Robots and Multirobot Systems, Springer Verlag.

Sklar, E., S. Parsons, S. L. Epstein, A. T. Ozgelen, J. P. Munoz, F. Abbasi, E. Schneider and M. Costantino (2012). Learning to Avoid Collisions. In Proceedings of AAAI Fall Symposium on Robots Learning Interactively from Human Teachers.

Ozgelen, A. T., E. Schneider, M. Costantino, J. P. Munoz, S. L. Epstein, S. Parsons and E. I. Sklar (2012). On Transfer from Multiagent to Multi-Robot Systems. In Proceedings of Autonomous Robots and Multirobot Systems (ARMS 2012)..

Sklar, E., S. Parsons, S. L. Epstein, A. T. Ozgelen, J. P. Munoz, F. Abbasi, E. Schneider and M. Costantino (2012) Applying FORR to human/multi-robot teams. In Human-Agent-Robot Teamwork Workshop at 7th ACM/IEEE International Conference on Human-Robot Interaction (HRI 2012)..

Sklar, E., Ozgelen, A. T., Munoz, J. P., Gonzalez, J., Manashirov, M., Epstein, S. L., et al. (2011). Designing the HRTeam Framework: Lessons Learned from a Rough-‘N-Ready Human/Multi-Robot Team. In Proceeding of the Autonomous Robots and Multirobot Systems Workshop.

Sklar, E. I., S. L. Epstein, S. Parsons, A. T. Ozgelen and J. P. Munoz (2011.A framework in which robots and humans help each other. In Proceeding of AAAI Symposium Help Me Help You: Bridging the Gaps in Human-Agent Collaboration. Palo Alto.

Sklar, E., S. Parsons, S. L. Epstein, A. T. Ozgelen, G. Rabanca, S. Anzaroo, J. Gonzalez, J. Lopez, M. Lustig, L. Ma, M. Manashiro, J. P. Munoz, S. B. Salazar and M. Schwartz (2010). Developing a Framework for Team-based Robotics Research. In Proceedings of AAAI 2010 Robotics Exhibition and Workshop..

Epstein, S. L. (1998). Pragmatic Navigation: Reactivity, Heuristics, and Search. Artificial Intelligence, 100 (1-2): 275-322.

Epstein, S. L. (1997). Representation and Reasoning for Pragmatic Navigation. In Proceedings of the AAAI Workshop on Spatial and Temporal Reasoning, Providence: AAAI. (pp.19-28)

Epstein, S. L. (1997). Spatial Representation for Pragmatic Navigation. In Proceedings of the Conference on Spatial Information Theory – COSIT ’97, 373-388. Laurel Highlands, PA: Springer Verlag. Best Paper Prize.

Epstein, S. L. (1996). Spatial Representation for Pragmatic Navigation. In Proceedings of the AAAI Spring Symposium on Cognitive and Computational Models of Spatial Representation, Stanford, CA: AAAI.

Epstein, S. L. (1995). On Heuristic Reasoning, Reactivity, and Search. In Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, 454-461. Montreal: Morgan Kaufmann.

Cognitive science

Kralik, J. D., J. H. Lee, P. S. Rosenbloom, P. C. Jackson, S. L. Epstein, O. J. Romero, R. Sanz, O. Larue, H. R. Schmidtke, S. W. Lee and K. McGreggor. (2018).Metacognition for a Common Model of Cognition. Procedia Computer Science145: 730-739. Also in Proceedings of BICA-2018.

Epstein, S.L., A. Aroor, M. Evanusa, E.I. Sklar, and S. Parsons (2015). Navigation with Learned Spatial Affordances. In Proceedings of CogSci 2015. Pasadena, CA.

Epstein, S.L., A. Aroor, M. Evanusa, E.I. Sklar, and S. Parsons (2015). Learning Spatial Models for Navigation, In Proceedings of the Conference on Spatial Information Theory (COSIT 2015).

Epstein, S.L., A. Aroor, M. Evanusa, E. Sklar, and S. Parsons (2015).Spatial Abstraction for Autonomous Robot Navigation. Cognitive Processing.

Ligorio, T., S. L. Epstein, R. J. Passonneau and J. B. Gordon 2010. What You Did and Didn’t Mean: Noise, Context, and Human Skill. In Proceedings of Cognitive Science — 2010.

Epstein, S.L. (2005). Thinking Through Diagrams: Discovery in Game Playing. In Proceedings of Spatial Cognition IV, LNAI 3343, Springer-Verlag, pp. 260-283.

Epstein, S. L. (2005). Making Interdisciplinary Collaboration Work. In Interdisciplinary Collaboration: An Emerging Cognitive Science. S.J. Derry, Schunn, C.D., and M.A. Gernsbacher, M.A. (Eds). United Kingdom: Lawrence Erlbaum.

Epstein, S. L. and Keibel, J.-H. (2002). Learning on Paper: Diagrams and Discovery in Game Playing. In Proceedings of Diagrams’02.

Epstein, S. L. (1994). For the Right Reasons: The FORR Architecture for Learning in a Skill Domain. Cognitive Science, 18 (3): 479-511.

Gelfand, J., Handelman, D., Lane, S., Rohde, D. & Epstein, S. (1994). Independent Controlled and Automatic Processing Streams and the Shifting of the Locus of Brain Activity during Skill Learning. In Proceedings of the Workshop on Intelligence, IEEE 9th International Symposium on Intelligent Control. Columbus, OH.

Gelfand, J., Handelman, D., Lane, S. and Epstein, S. (1994). Models of the Shifting of the Locus of Brain Activity during Skill Learning. Abstract. In Proceedings of the Inaugural Meeting of the Cognitive Neuroscience Society.

Gelfand, J., Handelman, D., Lane, S. and Epstein, S. (1994). Adapting Human Functional Architectures and Behaviors for Intelligent Machines. Handbook of Neuropsychology, ed. F. Boller and J. Grafman. New York: Elsevier. 361-376.

Epstein, S. L. (1992). Capitalizing on Conflict: The FORR Architecture. In Proceedings of the Workshop on Computational Architectures for Supporting Machine Learning and Knowledge Acquisition, Ninth International Machine Learning Conference, Aberdeen, Scotland

Epstein, S. L. (1992). The Interaction of Memory and Explicit Concepts in Learning. In Proceedings of the Fourteenth Annual Conference of the Cognitive Science Society, 570-575. Bloomington, IN: Lawrence Erlbaum.

Problem solving, learning, and constraints

Epstein, S. L. and E. Osisek (2016). I’ll know it when I see it: Toward Cognitively Plausible Recommendations. Cognitum 2016. New York, NY.

Epstein, S. L. (2015). Wanted: Collaborative Intelligence. Artificial Intelligence 221: 36-45.

Epstein, S. L., M. Evanusa and A. Aroor (2015). In Preparation for Joint Action. In Proceedings of Towards a Framework for Joint Action, Workshop at HRI-2015.Portland, OR.

Epstein, S. L., X. Yun and L. Xie (2013). Multi-Agent, Multi-Case-Based Reasoning. In Proceedings of International Conference on Case-Based Reasoning, Saratoga Springs, NY.

Epstein, S. L., and Petrovic, S. (2012). Learning Expertise with Bounded Rationality and Self-awareness. In Autonomous Search, E. M. Y. Hamadi, F. Saubion (Ed.), : Springer

Epstein, S. L., Osisek, E., Hixon, B., & Passonneau, R. J. (2012). Similarity and plausible recommendations. Advances in Cognitive Systems, 2, 185-202

Yun, X. and S.L. Epstein (2012), A Hybrid Paradigm for Adaptive Parallel Search. In Proceedings of Eighteenth Conference on Principles and Practice of Constraint Programming (CP-2012).

Yun, X. and S. L. Epstein (2012). Adaptive Parallelization for Constraint Satisfaction Search. In Proceedings of Symposium on Combinatoric Search (SOCS-2012).

Yun, X. and S. Epstein (2012). Learning Algorithm Portfolios for Parallel Execution. LION-2012, Springer-Verlag..

Li, X. and S. L. Epstein (2010). Learning cluster-based structure to solve constraint satisfaction problems. Annals of Mathematics and Artificial Intelligence.

Epstein, S. L. and X. Yun (2010). From Unsolvable to Solvable: An Exploration of Simple Changes. In Proceedings of WARA-10.

Li, X. and S. L. Epstein (2010). Visualization for Structured Constraint Satisfaction Problems. In Proceedings of AAAI Workshop on Visual Representations and Reasoning.

Epstein, S. L., & Petrovic, S. (2012). Learning Expertise with Bounded Rationality and Self-awareness.. In Metareasoning: Thinking about Thinking, MIT Press. Ed. M. T. Cox and A. Raja.

Epstein, S. L. (2009). Integrating a Portfolio of Representations to Solve Hard Problems. In Proceedings of the AAAI Fall Symposium on Multi-representational Architectures for Human-level Intelligence.

Epstein, S. L. and X. Li (2009).Cluster-based Modeling for Constraint Satisfaction Problems. In Proceedings of the IJCAI Workshop on Learning Structural Knowledge from Observations.

Epstein, S. L., & Li, X. (2009). Cluster Graphs as Abstractions for Constraint Satisfaction Problems. In Proceedings of SARA-09.

Epstein, S. L. and X. Li (2009). Search on Constraint Satisfaction Problems with Sparse Secondary Structure. In Proceedings of International Symposium on Combinatorial Search (SoCS-09).

Petrovic, S. and S. L. Epstein (2008). Tailoring a Mixture of Search Heuristics. Constraint Programming Letters 4: 15-38.

Epstein, S. L. (2008). Building a Constraint Solver that Learns. In Proceedings of the AAAI Fall Symposium on BIologically Inspired Computer Architecture, Arlington VA. AAAI.

Epstein, S. L. (2008). Optimistic Problem Solving. In Proceedings of the AAAI Fall Symposium on Naturally Inspired Artificial Intelligence, Arlington VA.

Epstein, S. L. and S. Petrovic (2008).Learning Expertise with Bounded Rationality and Self-awareness. In Proceedings of AAAI Workshop on Metareasoning, Chicago, AAAI.

Zhang, Z. and S. L. Epstein (2008).Learned Value-Ordering Heuristics for Constraint Satisfaction. In Proceedings of STAIR-08 Workshop at AAAI-2008.

Petrovic, S. and S. L. Epstein (2007). Random Subsets Support Learning a Mixture of Heuristics. International Journal on Artificial Intelligence Tools 20(10): 1-17. (An earlier, less detailed version appeared as Petrovic, S. and S. L. Epstein (2007). Learning to Solve Constraint Problems. ICAPS-07 Workshop on Planning and Learning, Providence RI.)

Petrovic, S. and S. L. Epstein (2007). Random Subsets Support Learning a Mixture of Heuristics. In Proceedings of FLAIRS-2007, Key West, AAAI.

Petrovic, S., S. L. Epstein and R. J. Wallace (2007). Learning a Mixture of Search Heuristics. In Proceedings of CP-07 Workshop on Autonomous Search, Providence, RI.

Petrovic, S. and S. L. Epstein (2007). Preferences Improve Learning to Solve Constraint Problems. In Proceedings of AAAI-07 Workshop on Preference for Artificial Intelligence.

Zhang, Z. and S.L. Epstein, (2007).Constraint Solving by Composition. In Proceedings of CP-07, Providence, RI.

Epstein, S. L. and R. J. Wallace (2006). Finding Crucial Subproblems to Focus Global Search. In Proceedings of ICTAI-2006, Washington, D.C., IEEE.

Epstein, S. L. (2006).In Support of Pragmatic Computation. In Proceedings of the AAAI Symposium on Cognitive Science Principles Meet AI-hard Problems, AAAI Spring Symposium, Palo Alto, CA, AAAI.

Petrovic, S. and S. L. Epstein. (2006). Full Restart Speeds Learning. In Proceedings of FLAIRS-2006.

Petrovic, S. and S. L. Epstein. (2006). Relative Support Weight Learning for Constraint Solving. In Proceedings of Workshop on Learning to Search at AAAI-2006, Boston,WS-06-11,115-122.

Epstein, S. L., E. C. Freuder and M. Wallace (2005). Learning to Support Constraint Programmers. Computational Intelligence 21(4): 337-371.

Epstein, S. L., E. C. Freuder, R. M. Wallace and X. Li. (2005). Learning Propagation Policies. In Proceedings of the Second International Workshop on Constraint Propagation and Implementation, Sitges, Spain, pp.1-15.

Epstein, S. L. (2004). A Cognitively-Oriented Architecture Confronts Hard Problems. In Proceedings of the AAAI Fall Symposium on Achieving Human-Level Intelligence. Washington, DC: AAAI.

Epstein, S.L. (2004). Metaknowledge for Autonomous Systems. In Proceedings of AAAI Spring Symposium on Knowledge Representation and Ontology for Autonomous Systems. AAAI. (pp. 61-68).

Epstein, S. L. and T. Ligorio. (2004). Fast and Frugal Reasoning Enhances a Solver for Really Hard Problems. In Proceedings of Cognitive Science (2004). Chicago: Lawrence Earlbaum, pp.351-356.

Epstein, S.L., E.C. Freuder, R. Wallace, A. Morozov and B. Samuels. (2002). The Adaptive Constraint Engine. In Principles and Practice of Constraint Programming — CP2002, LNCS 2470. Berlin: Springer Verlag.

Epstein, S. L. and G. Freuder. (2001). Collaborative Learning for Constraint Solving. In Principles and Practice of Constraint Programming — CP2001, LNCS 2239. Berlin: Springer Verlag.

Epstein, S. L. (1990). Learning to Play an Expert. Abstract. In Proceedings of the Eighth International Conference on Cybernetics and Systems, 18.

Natural language processing

Epstein, S. L., Osisek, E., Hixon, B., & Passonneau, R. J. (2012). Similarity and plausible recommendations. Advances in Cognitive Systems, 2, 185-202

Passonneau, R.J., Epstein, S.L. Ligorio, T.: Naturalistic Dialogue Management for Noisy Speech Recognition. IEEE Journal of Special Topics in Signal Processing. Advances in Spoken Dialogue Systems and Mobile Interfaces., 6, 928-942 (2012)

Epstein, S. L., R. J. Passonneau, T. Ligorio and J. Gordon 2012. Toward Habitable Assistance from Spoken Dialogue Systems. Innovative Applications of Artificial Intelligence (IAAI-2012).

Hixon, B., R. J., Passonneau, and S. L. Epstein 2012. Semantic Specificity in Spoken Dialogue Requests. SIGDIAL 2012.

Passonneau, R. J., S. L. Epstein, T. Ligorio, J. Gordon and P. Bhutada 2010. Learning about Voice Search for Spoken Dialogue Systems. In Proceedings of NACL-HLT. . Nominated for best paper prize.

Epstein, S. L., R. J. Passonneau, T. Ligorio and J. Gordon (2012). Data Mining to Support Human-Machine Dialogue for Autonomous Agents. In Proceedings of Agents and Data Mining Interaction (ADMI2011), Springer-Verlag.

Epstein, S. L., R. J. Passonneau, J. Gordon and T. Ligorio (2011). The Role of Knowledge and Certainty in Understanding for Dialogue. In Proceedings of the AAAI Fall Symposium on Advances in Cognitive Systems. Washington, DC.

Hixon, B., E. Schneider and S. L. Epstein (2011). Phonemic Similarity Metrics to Compare Pronunciation Methods. In Proceeding of Interspeech 2011. Florence, Italy.

Passonneau, R., Epstein, S. L., Ligorio, T., & Gordon, J. (2011). Embedded Wizardry. In Proceeding of SIGDIAL 2011.

Gordon, J., Epstein, S. L., & Passonneau, R. J. (2011). Learning to Balance Grounding Rationales for Dialogue Systems. In Proceeding of SIGDIAL-11.

Gordon, J. B., R. J. Passonneau and S. L. Epstein (2011). Helping Agents Help Their Users Despite Imperfect Speech Recognition. In Proceeding of AAAI Symposium Help Me Help You: Bridging the Gaps in Human-Agent Collaboration. Palo Alto.

Ligorio, T., S. L. Epstein and R. J. Passonneau 2010. Wizards’ Dialogue Strategies to Handle Noisy Speech Recognition. In Proceedings of IEEE-SLT workshop, Berkeley CA.

Epstein, S. L., R. J. Passonneau, J. Gordon and T. Ligorio (2010). Toward Spoken Dialogue as Mutual Agreement. In Proceedings of AAAI Workshop on Metacognition for Robust Social Systems.

Passonneau, R. J., Epstein, S. L., Gordon, J. B., & Ligorio, T. (2009). Seeing What You Said: How Wizards Use Voice Search Results. In Proceedings of the IJCAI-09 Workshop on Knowledge and Reasoning in Practical Dialogue Systems.

Passonneau, R., & Epstein, S. L. (2009). Help Me Understand You: Addressing the Speech Recognition Bottleneck. In Proceedings of AAAI Spring Symposium on Agents that Learn from Human Teachers.

Bioinformatics

Yun, X., W. Han, S. L. Epstein and L. Xie (2013). A Case-Based Meta-Learning Algorithm Boosts the Performance of Structure-Based Virtual Screening. In Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2013), Shanghai, China.

Yun, X., S. L. Epstein, W. Han and L. Xie (2013). Case-Based Meta-Prediction for Bioinformatics. In Proceedings of IAAI-13 Innovative Applications of Artificial Intelligence, Bellevue, WA.

Coronado, J. E., S. Mniemneh, S. L. Epstein, W.-G. Qiu and P. N. Lipke (2007). Conserved Processes and Lineage-Specific Proteins in Fungal Cell Wall Evolution. Eukaryotic Cell 6(12): 2269-77.

Epstein, S. L., X. Li, R. Valdez, S. Grayevsky, E. Osisek, X. Yun and L. Xie 2012. Discovering Protein Clusters AAAI Fall Symposium on Discovery Informatics: The Role of AI Research in Innovating Scientific Processes.

Coronado, J. E., O. Attie, S. L. Epstein, W.-G. Qiu and P. N. Lipke (2007). Discovery of Recurrent Sequence Motifs in Saccharomyces cerevisiae Cell Wall Proteins. MATCH Communications in Mathematical and Computer Chemistry 58: 281-299.

Coronado, J., O. Attie, S. L. Epstein, W. Qiu and P. N. Lipke. (2006). Composition-modified Matrices Improve Homolog Identification for Low-complexity Yeast Glycoproteins. Eukaryotic Cell 5(4): 6628-637.

Coronado, J., O. Attie, S. L. Epstein, W.-G. Qiu and P. N. Lipke. (2005). Alignment of low-complexity glycoprotein sequences: composition-modified scoring matrices allow alignment of yeast cell wall proteins. Glycobiology. 15: 1204-5, 2005

Romov, P., L. Fubin, P. N. Lipke, S. L. Epstein and W.-G. Qiu.(2006). Comparative genomics reveals long, evolutionarily-conserved, low complexity islands in yeast proteins Journal of Molecular Evolution 63(3): 415-425.

Game Playing and Machine Learning

Epstein, S.L., 2022. Playing for More than the Win, In Proceedings of the AAAI Fall 2022 Symposium on Thinking Fast and Slow and Other Cognitive Theories in AI.

Lock, E. and Epstein, S. L. (2004). Learning and Applying Competitive Strategies. In Proceedings of AAAI-04. San Jose: 354-359.

Epstein, S. L. (2002). Game Playing. In Encyclopedia of Cognitive Science, London: Macmillan Reference Ltd.

Epstein, S.L.(2001). Learning to Play Expertly: A Tutorial on Hoyle. In Machines That Learn to Play Games, Huntington, NY: Nova Science.

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. T. (1998). Learning Game-Specific Spatially-Oriented Heuristics. Constraints, 3 (2-3): 239-253.

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 for Game Learning. In Proceedings of the Twentieth Annual Meeting of the Cognitive Science Society. Abstract.

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 in 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. (pp51-55).

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

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:

Design

Glasgow, J., Epstein, S. L., Meurice, N., Becue, A. and Vercauteren, D. P. (2004). Spatial Motifs in Design. In Proceedings of Visual and Spatial Reasoning in Design ’04. Cambridge, MA.

Glasgow, J. and Epstein, S.L. (2003). Issues in Computational Spatial Imagery. In Proceedings of the Ninth European Workshop on Imagery and Cognition (EWIC 2003). Pavia, Italy.

Chaker, W., Moulin, B. and Epstein, S. L.(2001). PADI: a Software to Support Park Design. In Proceedings of the GEOIDE Third Annual Conference. Fredericton, CA.

Gancet, J., Moulin, B. and Epstein, S. L. (2001). Using Software Agents to Simulate the Use of Geographic Spaces. In Proceedings of the GEOIDE Third Annual Conference. Fredericton, CA.

Epstein, S.L. (2001). Toward autonomous layout design – An AI Approach. In Proceedings of Visual & Spatial Reasoning in Design ’01. Bellagio, IT: 325-344.

Epstein, S. L., Moulin, B., Chaker, W., Glasgow, J. and Gancet, J. (2001). Pragmatism and Spatial Layout Design. In Proceedings of COSIT ’01 – Conference on Spatial Information Theory, Morro Bay, CA: Springer Verlag.

Epstein, S. L. (1998). Toward Design as Collaboration. In Proceedings of the Fifteenth National Conference on Artificial Intelligence, Madison, WI: AAAI.

Discovery in Mathematics

Epstein, S. L. (2008). Knowledge Representation in Automated Scientific Discovery. In Proceedings of the AAAI Fall Symposium on Automated Scientific Discovery, Arlington VA. AAAI.

Epstein, S. L. (1987). On the Discovery of Mathematical Theorems. In Proceedings of the Tenth International Joint Conference on Artificial Intelligence, pp.194-197. Los Altos: Morgan Kaufmann.

Epstein, S. L., et al. (1987). Theoretical and Empirical Approaches.The Role of Language in Problem Solving 2, ed. J. C. Boudreaux, B. W. Hamill and R. N. Jernigan. New York: North-Holland.

Epstein, S. L. (1992). The Role of Memory and Concepts in Learning. Minds and Machines, 2: 239-265.

Epstein, S. L. and Sridharan, N. S. (1991). Knowledge Representation for Mathematical Discovery – Three Experiments in Graph Theory. Applied Intelligence, 1 (1): 7-33.

Epstein, S. L. (1988). Learning and Discovery: One System’s Search for Mathematical Knowledge. Computational Intelligence, 4 (1): 42-53.

Epstein, S. L. (1988). On the Discovery of Mathematical Concepts. International Journal of Intelligent Systems, 3 (2): 167-178.

Epstein, S. L. (1987). Languages for Problem Solving in Graph Theory. In J. C. Boudreaux, B. W. Hamill, & R. N. Jernigan (Ed.), The Role of Language in Problem Solving 2 (pp. 261-300). New York: North-Holland.

Epstein, S. L. (1987). On the Discovery of Mathematical Theorems. In Proceedings of the Tenth International Joint Conference on Artificial Intelligence, pp.194-197. Los Altos: Morgan Kaufmann.

Education

Eaton, E. and Epstein, S.L. (2003) Artificial Intelligence in the CS2023 Undergraduate Computer Science Curriculum: Rationale and Challenges.. In Proceedings of EAAI-2024.

Kumar, A., Anderson, M.D., Becker, B.A., Pias, M., Oudshoom, M., Jalote, P., Servin, C. Aly, S.G., Blumenthal, R.L., Epstein, S.L. (2023) .A Combined Knowledge and Competency (CKC) Model for Computer Science Curricula. ACM Inroads, 14(3):22-29.

Thesis

Epstein, S. L. Knowledge Representation in Mathematics: A Case Study in Graph Theory. Ph.D. thesis, Department of Computer Science, Rutgers University. (1983).