Using primary source material, this course will explore psychological work in knowledge representation. In addition, we will focus on some of the links between psychological studies of this topic and similar examinations in other areas of cognitive science.
Markman, A. B. (1999). Knowledge representation. Mahwah, NJ: Lawrence Erlbaum Associates.
The other readings will be available at least one week before class on the Blackboard system. On some weeks, a student will be asked to lead the discussion. Leaders for a particular class may have to read one or two additional articles to get a better background in the topic for that week. The class leader for that week should prepare a brief (30-40 min.) presentation on the topic for the week, and should come prepared with discussion questions.
In order to get into class each week, everyone has to turn in a `ticket'. Tickets are 1-2 page reactions to the readings for the week. The tickets should not be a summary of what you read. Rather, I'd like your opinions. Is the representation suggested by the authors sufficient to do what they claim? Would a representation we discussed in a previous class be better suited to this problem. What do you think are the main advances of the work, or how does it fail to take into account other work. Feel free to draw on your own expertise in other areas of psychology or from other disciplines. If you think a particular representation would be helpful for some problem you have been thinking about, say so. If you felt a particular article was confusing, say that too.
For those of you taking this class for credit, your grade will depend primarily on two things: your tickets and a paper. For the paper, you have a number of options. One possibility is to find an area of research that you think is interesting. If you are currently involved in a research project, you may use that area. Trace the evolution of the representation-process pairs that have been used to study that area. Then, describe what you think is an adequate representation for that area. You might also want to sketch a set of empirical studies that you might run to test your hypotheses. Another possibility would be to outline the simulation of a process. This option is well suited to people with some background in computational modeling or programming. The main idea is to expand succinctly on a good research question. I expect that the papers will be about 20 pages long. In order to facilitate writing the paper, everyone should turn in a paper proposal no later than March 1. The proposal should be at least a couple of paragraphs describing what you would like to do.
Palmer, S.E. (1978). Fundamental aspects of cognitive representations. In E.
Rosch and B.B. Lloyd (Eds.) Cognition and Categorization. Hillsdale, NJ: Erlbaum.
Marr, D. (1982). Vision. New York: W.H. Freeman and Company. Chapter 1.
|Feb. 1||Introduction to Spatial representations||Jordan Davison||2||Edelman, S. (1998). Representation is representation of similarities. Behavioral and Brain Sciences, 21, 449-498.
Knapp, A.G., & Anderson, J.A. (1984). Theory of categorization based on distributed memory storage. Journal of Experimental Psychology: Learning, Memory, and Cognition, 10, 616-637.
Landauer, T.K. & Dumais, S.T. (1997). A solution to Plato's problem: The latent semantic analysis theoyr of acquisition, induction and representation of knowledge. Psychological Review, 104, 211-240.
Rips, L.J., Shoben, E.J. & Smith, E.E. (1973). Semantic distance and the verification of semantic relations. Journal of Verbal Learning and Verbal Behavior, 12, 1-20.
|Feb. 8||Featural representations||Nick Gaylord||3||
Tversky, A. (1977). Features of similarity. Psychological Review, 84(4), 327-352.
Martin, A., Haxby, J.V., Lalonde, F.M., Wiggs, C.L., & Ungerleider, L.G. (1995). Discrete cortical regions associated with knowledge of color and knowledge of action. Science, 270, 102-105.
Damasio, H., Grabowski, T.J., Tranel, D., Hichwa, R.D., & Damasio, A.R. (1996). A neural basis for lexical retrieval. Nature, 380, 499-505.
|Feb. 15||Semantic Networks||Brandon Wiley||4||
Anderson, J.R. (1983). A spreading activation theory of memory. Journal of verbal learning and verbal behavior, 22, 261-295.
Collins, A.M., & Loftus, E.F. (1975). A spreading-activation theory of semantic priming. Psychological Review, 82, 407-428.
McClelland, J.L. & Rumelhart, D.E. (1981). An interactive activation model of context effects in letter perception: Part I, An account of basic findings. Psychological Review, 88, 375-407.
|Feb. 22||Introduction to structured representations||Aron Weinberg||5||Jackendoff, R. (2002). Foundations of Language. New York: Oxford University Press. (Chapters 1 and 11)
Love, B.C., & Markman, A.B. (2003). The non-independence of stimulus properties in category learning. Memory and Cognition, 31, 790-799.
Marcus, G.F. (2000). Two kinds of representation. In E. Dietrich & A.B. Markman (Eds.) Cognitive Dynamics (pp. 79-88). Mahwah, NJ: Lawrence Erlbaum Associates.
|Mar. 1||Production Systems||Todd Hutner||
Anderson, J.R. (1993). Rules of the Mind. Hillsdale, NJ: Lawrence Erlbaum Associates. (Chapters 1 and 2)
Newell, A. (1990). Unified Theories of Cognition. Cambridge, MA: Harvard University Press. (Chapter 2).
|Mar. 8||Structure in perception||Dustin Adams||6||
Hinton, G.E. (1979). Some demonstrations of the effects of structural descriptions in mental imagery. Cognitive Science, 3, 231-250.
Hummel, J.E. (2000). Where view-based theories break down: The role of structure in human shape perception. In E. Dietrich & A.B. Markman (Eds.) Cognitive Dynamics (pp. 157-185). Mahwah, NJ: Lawrence Erlbaum Associates.
Barenholtz, E., & Tarr, M.J. (2007). Reconsidering the role of structure in vision. The Psychology of Learning and Motivation, 47, 157-180.
Biederman, I. (1987). Recognition-by-components: A theory of human image understanding. Psychological Review, 94, 115-147.
|Mar. 22||Higher order structure||Jennifer Landa||7||
Falkenhainer, B.F., Forbus, K.D., & Gentner, D. (1989). The structure
mapping engine: Algorithm and examples. Artificial Intelligence,
Gentner, D. & Markman, A.B. (1997). Structural alignment in analogy and similarity. American Psychologist, 52, 45-56.
Doumas. L. A. A., Hummel, J. E., & Sandhofer, C. M. (2008). A theory of the discovery and predication of relational concepts. Psychological Review, 115, 1 - 43.
|Mar. 29||Scripts and schemas.||Kevin Smith||
Anderson, R.C. & Pichert, J.W. (1978). Recall of previously unrecallable information following a shift in perspective.Journal of Verbal Learning and Verbal Behavior, 17, 1-12.
Bransford, J.D., & Johnson, M.K. (1973). Considerations of some problems of comprehension. In W.G. Chase (Ed.) Visual information processing (pp. 383-438). New York: Academic Press
Schank, R.C., & Abelson, R.P. (1977). Scripts Plans Goals and Understanding. Hillsdale, NJ: Erlbaum. (Chapter 3)
Schank, R.C. (1982). Dynamic Memory, New York: Cambridge University Press. (Chapters 4, 5 and 6).
|Apr. 5||The priority of the specific
and Case-based reasoning
Bassok, M., Chase, V.M., & Martin, S.A. (1998). Adding apples and oranges: Semantic constraints on application of formal rules. Cognitive Psychology, 35, 99-134.
Medin, D.L., & Ross, B.H. (1989). The specific character of abstract thought: Categorization, problem-solving and induction. In R.S. Sternberg (Ed.) Advances in the Psychology of Human Intelligence. Hillsdale, NJ: Lawrence Erlbaum Associates.
Kolodner, J. (1993). Case-Based Reasoning. San Mateo, CA: Morgan Kaufmann Publishers, Inc. (Chapter 2).
|Apr. 12||Mental models and diagrams for reasoning||Mark Bayer||9||Cheng, P.C.H. (2002). Electrifying diagrams for learning: Principles for complex representational systems. Cognitive Science, 26, 685-736.
Johnson-Laird, P.N. (1983). Mental models. Cambridge, MA: Harvard University Press (Chapters 5+6)
Novick, L.R. & Hurley, S.M. (2001). To matrix, network, or hierarchy: That is the question. Cognitive Psychology. 42(2), 158-216.
|Apr. 19||Mental models and causality||
Forbus, K. D. (1984). Qualitative process theory. Artificial Intelligence, 24(1), 85-168.
Rosenblit, L., & Keil, F. C. (2002). The misunderstood limits of folk science: An illusion of explanatory depth. Cognitive Science, 26, 521-562.
Wolff, P. (2007). Representing causation. Journal of Experimental Psychology: General, 136(1), 82-111.
|Apr. 26||Embodied Cognition||
Barsalou, L.W. (1999). Perceptual Symbol Systems. Behavioral and Brain Sciences, 22, 577-660.
Tamir, M., Robinson, M.D., Clore, G.L., Martin, L.L., & Whitaker, D.J. (2004). Are we puppets on a string? The contextual meaning of unconscious expressive cues. Personality and Social Psychology Bulletin, 30, 237-249.
Anderson, M.L. (2003). Embodied cognition: A field guide. Artificial Intelligence, 149(1), 91-130.
Wilson, M. (2002). Six views of embodied cognition. Psychonomic Bulletin and Review, 9, 625-636
|May 3||Representations, who needs 'em?||10||Brooks, R. (1991). Intelligence without representation. Artificial Intelligence, 47, 139-159.
Markman, A.B., & Dietrich, E. (2000). In defense of representation. Cognitive Psychology, 40, 138-171.
Spivey, M.J., & Dale, R. (2006). Continuous dynamics in real-time cognition. Current Directions in Psychological Science, 15, 207-211.
van Gelder, T., & Port, R.F. (1995). It's about time: An overview of the dynamical approach to cognition. In R.F. Port & T. van Gelder (Eds.) Mind as Motion. Cambridge, MA: The MIT Press.