Professor of Computer Science
echown@bowdoin.edu
207-725-3084
Computer Science
Searles Science Building - 221
Eric Chown Sarah Harmon
What is computer science, what are its applications in other disciplines, and what is its impact in society? A step-by-step introduction to the art of problem solving using the computer and programming. Provides a broad introduction to computer science and programming through real-life applications. Weekly labs provide experiments with the concepts presented in class. Assumes no prior knowledge of computers or programming. Final examination grade must be C or better to serve as a prerequisite for Computer Science 2101.
Eric Chown
Intended for students with some programming experience, but not enough to move directly into Data Structures. An accelerated introduction to the art of problem solving using the computer and the Python programming language. Weekly labs and programming assignments focus on "big data" and its impact on the world.
Eric Chown
Explores the principles and techniques involved in programming computers to do tasks that would require intelligence if people did them. State-space and heuristic search techniques, logic and other knowledge representations, reinforcement learning, neural networks, and other approaches are applied to a variety of problems with an emphasis on agent-based approaches.
Eric Chown
An in-depth investigation of an aspect of the relationship of digital technologies with human development, history, education, ethics, the environment, or social practices. Draws on topics including text analysis, network analysis, and image analysis. In turn, these topics are used as a lens to examine real-world issues, such as identity and privacy, both to expand the understanding of such issues as well as to better understand the power and also the limitations of the methodologies. Students apply the models offered by readings and the methodologies of digital and computational studies to a semester-long project that investigates an aspect of computation in the context of their major or minor field of study.
Besides teaching computer science courses in artificial intelligence, cognitive architecture, and computer programming, Eric Chown also enjoys researching the learning in humans and machines. Three years ago, he was awarded a five-year National Science Foundation Faculty Early Career Development Grant that was used to buy specialized robots for his project - "Computational Models of Space in Navigation and Other Domains." Chown has used these robots in several of his classes.
Journals
Chown, E. (1999). Making predictions in an uncertain world: Environmental structure andcognitive maps. Adaptive Behavior, 1-17.
Chown, E., Kaplan, S. & Kortenkamp, D. (1995). Prototypes, Location and AssociativeNetworks (PLAN): Towards a unified theory of cognitive mapping. Cognitive Science., 19, 1-52.
Kaplan, S., Sonntag, M. & Chown, E. (1991) Tracing recurrent activity in cognitive elements(TRACE): A model of temporal dynamics in a cell assembly. Connection Science, 3, 179206.
Highly Refereed Conferences
Chown, E. (2002). Reminiscence and arousal: A connectionist model. To appear in theProceedings of the Twenty Fourth Annual Meeting of the Cognitive Science Society.
Chown, E. & Dietterich, T. G. (2000). A divide and conquer approach to learning from priorknowledge. In Proceedings of the Seventeenth International Conference on Machine Learning, Langley, P. (ed.), Morgan Kauffman, 143-150.
Chown, E., Jones, R.M., & Henninger, A.E. (2002). An architecture for emotional decision-making agents. To appear in the proceedings of The First Annual Conference on Autonomous Agents & Multiagent Systems
Forbell, E., & Chown, E. (2000).Lexical contact during speech perception: A connectionist model. In Proceedings of the Twenty Second Annual Meeting of the Cognitive Science Society.
Henninger, A.E., Jones, R.M. & Chown (2003). Behaviors that emerge from emotion andcognition: Implementation and evaluation of a symbolic-connectionist architecture. To appear in the proceedings of The Second Annual Conference on Autonomous Agents & MultiagentSystem.
Kortenkamp, D. & Chown, E. (1993). A directional spreading activation network for mobilerobot navigation. From Animals to Animats 2, Proceedings of the Second International Conference on Simulation of Adaptive Behavior, Meyer, J.-A., Roitblat H. L. and Wilson,S.W. (eds.), MIT-Press.
Book Chapters
Chown, E. & Boots, B. (2005). Learning Cognitive Maps: Finding Useful Structure in an Uncertain World. To appear in Jefferies, M. & Yeap, A. (eds.) Robot and Cognitive Approaches to Spatial Mapping.
Chown, E. (2004) Cognitive Modeling. In Tucker, A. (ed.) Computer Science Handbook. Chapman & Hall.
PDF preprint »
Chown, E. (1999). Error tolerance and generalization in cognitive maps: Performance withoutprecision. In Golledge, R. (ed.) Wayfinding Behavior: Cognitive Mapping and Other Spatial Processes., 349-369 The Johns Hopkins University Press.
Commentaries
Chown, E. (1995). Reverberation reconsidered: On the path to cognitive theory. Behavioral andBrain Sciences, 18, 628-629.
Chown, E., Booker, L.B., & Kaplan, S. (2002). Perception, Action Planning, and CognitiveMaps. To appear in Behavioral and Brain Sciences.
Chown, E. & Kaplan, S. (1992). Active symbols, limited storage and the power of naturalintelligence. Behavioral and Brain Sciences, 15:3, 442-443.
Other
Chown, E., Foil, G., Work, H., & Zhuang, Y. (2006). AiboConnect: A simple programming environment for robotics. To appear in The proceedings of the 19th International FLAIRS Conference.
PDF preprint »
Henninger, A.E., Jones, R.M. & Chown, E. (2003). Behaviors that emerge from emotion and cognition: Implementation and evaluation of a symbolic-connectionist architecture. To appear in The proceedings of Autonomous Agents and Multi-Agent Systems '03.
PDF preprint »
Chown, E., (2002). Reminiscence and arousal: a connectionist model. In The proceedings of the 24th annual meeting of the Cognitive Science Society, 234-239.
PDF preprint »
Chown, E., Jones, R.M., & Henninger, A.E. (2002). An architecture for emotional decision-making agents. In The proceedings of Autonomous Agents and Multi-Agent Systems '02.
PDF preprint »
Jones, R.M., Henninger, A.E., & Chown, E. (2002). Interfacing emotional behavior moderators with intelligent synthetic forces. Proceedings of the 11th Computer Generated Forces and Behavior Representation Conference.
PDF preprint »
Henninger, A.E., Jones, R.M. & Chown, E. (2002). Behaviors that emerge from emotion and cognition: A first evaluation. Proceedings of the '02 Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC). Orlando, FL.
PDF preprint »
Henninger, A.E., Jones, R.M., & Chown, E. (2001). A symbolic-connectionist framework for representing emotions in computer generated forces. Proceedings of the '01 Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC). Orlando, FL.
PDF preprint »
Chown, E., & Dietterich, T.G. (2000). Learning in the Presence of Prior Knowledge: A Case Study Using Model Calibration. Poscript preprint. In the Proceedings of the Seventeenth International Conference on Machine Learning. P. Langley (ed.). Morgan Kauffman, pp 143-150.
Chown, E. (2000). Gateways: An approach to parsing spatial domains. In ICML-2000 Workshop on Machine Learning of Spatial Knowledge, 1-6.
Jones, R.M., Chown, E., & Henninger, A.E. (2001). A hybrid symbolic-connectionist approachto modeling emotions. In AAAI Fall Symposium Emotional and Intelligent II: The Tangled Knot of Social Cognition. Technical Report FS-01-02. AAAI Press.
Henninger, A.E., Jones, R.M., and Chown, E. (2002). Behaviors that emerge from emotion andcognition: A first evaluation. In the Proceedings of Interservice/Industry Training Simulation and Education Conference (I/ITSEC), 2002. Orlando, FL
Henninger, A.E., Jones, R.M., and Chown, E. (2001). Framework for Attention, Cognition andEmotion in Synthetic Forces. In the Proceedings of Interservice/Industry Training Simulation and Education Conference (I/ITSEC), November 26-29, 2001. Orlando, FL.
Chown, E. (1994). Consolidation and Learning: A Connectionist Model of Human Credit Assignment. Doctoral dissertation. The University of Michigan.
(1999). Fitting Parameters to Ecosystem Models Using Surface Data. 1999 NASA Workshop onData Mining and Data Fusion
(2000). Gateways: An approach to parsing spatial domains. ICML-2000 Workshop on MachineLearning of Spatial Knowledge.
Undergraduate Honors Thesis Supervision
Eric Forbell, Bowdoin College
Anthony Roy, Bowdoin College
Doug Vail, Bowdoin College
Byron Boots, Bowdoin College
Masters Committee Membership
Russ Tedrake, University of Michigan
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