Publications in Category Learning

Prezenski, S. and Russwinkel, N. (2016). Towards a general model of repeated app usage. In D. Reitter & F. E. Ritter (Eds.), Proceedings of the 14th International Conference on Cognitive Modeling. University Park, PA: Penn State.

Thomson, R. Lebiere, C., Bennati, S., Shakarian, P., & Nunes, E. (2015). Malware Identification Using Cognitively-Inspired Inference. In Proceedings of the 24th Annual Behavior Representation in Modeling and Simulation Conference. Washington, DC.

Lebiere, C., Bennati, S., Thomson, R., Shakarian, P., & Nunes, E. (2015). Functional Cognitive Models of Malware Identification. In N. Taatgen (Ed), Proceedings of the 13th Annual Conference on Cognitive Modeling. Groningen, Netherlands.

Paik, J., Pirolli, P., Dong, W., Lebiere, C., & Thomson, R. (2013). An ACT-R Model of Sensemaking in a Geospatial Intelligence Task. In Proceedings of the 22nd Annual Conference on Behavior Representation in Modeling and Simulation.

Lebiere, C., Pirolli, P., Thomson, R., Paik, J., Rutledge-Taylor, M., Staszewski, J., & Anderson, J. (2013). A Functional Model of Sensemaking in a Neurocognitive Architecture. Computational Intelligence and Neuroscience; Special Issue on Neurocognitive Models of Sense Making.

Rutledge-Taylor, M., Lebiere, C., Thomson, R., Staszewski, J., & Anderson, J. R. (2012). A Comparison of Rule-Based versus Exemplar-Based Categorization Using the ACT-R Architecture. In Proceedings of the 21st Annual Behavior Representation in Modeling and Simulation Conference.

Thomson, R., Lebiere, C., Rutledge-Taylor, M., Staszewski, J., & Anderson, J. R. (2012). Understanding Sensemaking Using Functional Architectures. In T. Jambrowski (Ed.) Proceedings of the 21st Annual Behavior Representation in Modeling and Simulation Conference. Dayton, OH.

Petrov, A. (in press). Category rating is based on prototypes and not instances: Evidence from feedback-dependent context effects. Journal of Experimental Psychology: Human Perception and Performance.

Brumby, D. P. & Hahn, U. (2007). Rules and exemplars in categorization: A computation exploration. In The 29th Annual Conference of the Cognitive Science Society. Nashville, Tennessee, USA.

Anderson, J. R., & Betz, J. (2001). A hybrid model of categorization. Psychonomic Bulletin and Review, 8, 629-647.

Anderson, J. R. & Matessa, M. (1998). The rational analysis of categorization and the ACT-R architecture. In M. Oaksford & N. Chater (Eds.) Rational models of cognition, pp. 197-217. Oxford: Oxford University Press.

Anderson, J. R. & Fincham, J. M. (1996). Categorization and sensitivity to correlation. Journal of Experimental Psychology: Learning, Memory, and Cognition, 22, 259-277.

Elliott, S. & Anderson, J. R. (1995). The effect of memory decay on predictions from changing categories. Journal of Experimental Psychology: Learning, Memory, and Cognition, 815-836.

Anderson, J. R. & Matessa, M. (1992). Explorations of an incremental, Bayesian algorithm for categorization. Machine Learning, 9, 275-308.

Anderson, J. R. & Matessa, M. (1991). An iterative Bayesian algorithm for categorization. In D. Fisher, M. J. Pazzani & P. Langley (Eds.), Concept Formation: Knowledge and Experience in Unsupervised Learning. San Mateo, CA: Morgan Kaufman.

Anderson, J. R. (1991). The adaptive nature of human categorization. Psychological Review, 98, 409-429.

Anderson, J. R., & Matessa, M. (1990). A rational analysis of categorization. In Proceedings of the Seventh International Machine Learning Conference, 76-84. Palo Alto, CA: Morgan Kaufman.

Elio, R., & Anderson, J. R. (1984). The effects of information order and learning mode on schema abstraction. Memory and Cognition, 12, 20-30.

Elio, R., & Anderson, J. R. (1981). The effects of category generalization and instance similarity on schema abstraction. Journal of Experimental Psychology: Human Learning and Memory, 7, 397-417.

Anderson, J. R., Kline, P. J., & Beasley, C. M. (1980). Complex learning processes. In R. Snow, P. Federico, and W. Montague (Eds.) Aptitude, learning, and instruction: Cognitive processes analyses, Volume II, 199-232. Hillsdale, NJ: Erlbaum.

Anderson, J. R., Kline, P. J., & Beasley, C. M. (1979). A general learning theory and its application to schema abstraction. In G. H. Bower (Ed.) The Psychology of Learning and Motivation, New York: Academic Press.

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Department of Psychology, Carnegie Mellon University