Psych239: Formal and Computational Approaches in Psychology and Cognitive Science (Spring 2011)

Grading

Registered students will be expected to write a final paper (roughly 10pp) exploring in depth a topic related to the course.

Schedule

• March 28
  Introduction:
  • Griffiths, T. L., Kemp, C., and Tenenbaum, J. B. (2008). Bayesian models of cognition. In Ron Sun (ed.), The Cambridge handbook of computational cognitive modeling.
  • Thomas, M. S. C. & McClelland, J. L. (2008). Connectionist models of cognition. In R. Sun (Ed). Cambridge handbook of computational psychology.
  • Optional:
    Chapter 1 of Marr's book "Vision" (pp 8-28, top).
    Rumelhart, D. E. & McClelland, J. L. (1985). Levels indeed! A response to Broadbent. Journal of Experimental Psychology: General, 114, 193-197.
    Probabilistic models of cognition. N. D. Goodman and J. B. Tenenbaum (online tutorial).
• April 4
  Grammar-based Bayesian models of concept learning:
  • A rational analysis of rule-based concept learning. N. D. Goodman, J. B. Tenenbaum, J. Feldman, and T. L. Griffiths (2008). Cognitive Science.
  • Learning Structured Generative Concepts. A. Stuhlmueller, J. B. Tenenbaum, and N. D. Goodman (2010). Proceedings of the Thirty-Second Annual Conference of the Cognitive Science Society.
  • Optional:
    Beyond Boolean logic: exploring representation languages for learning complex concepts. S. T. Piantadosi, J. B. Tenenbaum, and N. D. Goodman (2010). Proceedings of the Thirty-Second Annual Conference of the Cognitive Science Society.
    A formal model of number word acquisition. S. T. Piantadosi, N. D. Goodman, and J. B. Tenenbaum (manuscript).
• April 11
  A connectionist model of word reading (and naive physics knowledge acquisition):
  • Understanding normal and impaired word reading: Computational principles in quasi-regular domains. Plaut, D. C., McClelland, J. L., Seidenberg, M. S., and Patterson, K. (1996). Psychological Review.
  • Optional:
    Schapiro, A. C. & McClelland, J. L. (2009). A connectionist model of a continuous developmental transition in the balance scale task. Cognition, 110(1), 395-411.
• April 18
  Algorithmic-level models of Bayesian inference:
  • Perceptual multistability as Markov chain Monte Carlo inference. Gershman, Vul, & Tenenbaum (2009).
  • Sanborn, A. N., Griffiths, T. L., & Navarro, D. J. (2010). Rational approximations to rational models: Alternative algorithms for category learning. Psychological Review, 117(4).
  • Optional:
    Modeling the effects of memory on human online sentence processing with particle filters. Levy, R., Reali, F., & Griffths, T. L. (2009).
• April 25
  Neural-level models of Connectionist processing:
  • Laing, C. R. & Chow, C. C. (2002). A spiking neuron model of binocular rivalry. Journal of Computational Neuroscience, 12, 39-53.
  • Wilson, H. R. (2007). Minimal physiological conditions for binocular rivalry and rivalry memory. Vision Research.
  • Optional:
    Vallabha, G. K. & McClelland, J. L. (2007). Success and failure of new speech category learning in adulthood: Consequences of learned Hebbian attractors in topographic maps. Cognitive, Affective and Behavioral Neuroscience, 7, 53-73.
    Vallabha, G. K., McClelland, J. L., Pons, F., Werker, J. & Amano, S. (2007). Unsupervised learning of vowel categories from infant-directed speech. Proceedings of the National Academy of Science, 104, 13273-13278.
• May 2
  Discussion of Gibbs Sampling and Boltzmann Machines.
• Optimal perceptual inference. Hinton and Sejnowski (1983).
• May 9
  Flexible category learning.
  • Vallabha, G. K., McClelland, J. L., Pons, F., Werker, J. & Amano, S. (2007). Unsupervised learning of vowel categories from infant-directed speech. Proceedings of the National Academy of Science, 104, 13273-13278.
  • Feldman, N. H., Griffiths, T. L., & Morgan, J. L. (2009). "Learning phonetic categories by learning a lexicon." Proceedings of the 31st Annual Conference of the Cognitive Science Society.
• May 16
  Compositionality in connectionist models.
  • McClelland, J.L., St. John, M., and Taraban, R. (1989). Sentence Comprehension: A Parallel Distributed Processing Approach. Language and Cognitive Processes, 4 , 287-335.
  • Bryant, B. D. & Miikkulainen, R. From Word Stream to Gestalt: A direct semantic parse for complex sentences. Technical Report AI98-274, AI Lab, University of Texas at Austin, Austin, TX, June 2001
• May 23
  Productivity and reuse in language: a probabilistic model.
  • T. J. O'Donnell, J. Snedeker, J. B. Tenenbaum, and N. D. Goodman (to appear). Productivity and reuse in language. Proceedings of the Thirty-Third Annual Conference of the Cognitive Science Society.