Abstract
Typically, models of category learning are verified through behavioral experiments with stimuli consisting of putatively independent dimensions such as shape, size, and color. The assumption of independence is critical in both the design of behavioral experiments and the development of models and theories of learning. Using the standard classification learning paradigm and a common stimulus set, the present work demonstrates that the assumption of independence is unwarranted. Systematic relations span stimulus dimensions and govern learning performance. For example, shape is not independent of size and color, because humans quantify size and color over shape when shape is relevant to the categorization. This quantification is reflected in natural language use (e.g., “blue triangle” as opposed to “triangle and blue”). In this example, color and size are predicates and shape is the argument. Across four experiments, the difficulty of mastering a classification rule can be predicted by the number of predicates that must be unbound in order to free rule-relevant stimulus dimensions.
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References
Anderson, J. (1991). The adaptive nature of human categorization.Psychological Review,98, 409–429.
Biederman, I., & Shiffrar, M. (1987). Sexing day-old chicks: A case study and expert systems analysis of a difficult perceptual learning task.Journal of Experimental Psychology: Learning, Memory, & Cognition,13, 640–645.
Bruner, J. S., Goodnow, J. J., & Austin, G. A. (1956).A study of thinking. New York: Wiley.
Edelman, S. (1999).Representation and recognition in vision. Cambridge, MA: MIT Press.
Feldman, J. (2000). Minimization of Boolean complexity in human concept learning.Nature,407, 630–633.
Garner, W. R. (1974).The processing of information and structure. Potomac, MD: Erlbaum.
Gentner, D. (1983). Structure-mapping: A theoretical framework for analogy.Cognitive Science,7, 155–170.
Gentner, D. (1989). The mechanisms of analogical learning. In S. Vosniadou & A. Ortony (Eds.),Similarity and analogical processing (pp. 199–241). Cambridge: Cambridge University Press.
Imai, M., Gentner, D., & Uchida, N. (1994). Children’s theories of word meaning: The role of shape similarity in early acquisition.Cognitive Development,9, 45–75.
Kahneman, D., Treisman, A., & Gibbs, B. J. (1992). The reviewing of object files: Object specific integration of information.Cognitive Psychology,24, 175–219.
Keane, M. T., Ledgeway, T., & Duff, S. (1994). Constraints on analogical mapping: A comparison of three models.Cognitive Science,18, 387–438.
Kolodner, J. (1993).Case-based reasoning. San Mateo, CA: Kaufmann.
Kruschke, J. K. (1992). ALCOVE: An exemplar-based connectionist model of category learning.Psychological Review,99, 22–44.
Landau, B., Smith, L. B., & Jones, S. S. (1988). The importance of shape in early lexical learning.Cognitive Development,3, 299–321.
Lockhead, G. R. (1966). Effects of dimensional redundancy on visual discrimination.Journal of Experimental Psychology,72, 95–104.
Love, B. C. (2001). Three deadly sins of category learning modelers.Behavioral & Brain Sciences,24, 687–688.
Love, B. C. (2002). Comparing supervised and unsupervised category learning.Psychonomic Bulletin & Review,9, 829–835.
Love, B. C. (2003). The multifaceted nature of unsupervised category learning.Psychonomic Bulletin & Review,10, 190–197.
Love, B. C., Medin, D. L., & Gureckis, T. (in press). SUSTAIN: A network model of human category learning.Psychological Review.
Markman, A. B. (1999).Knowledge representation. Mahwah, NJ: Erlbaum.
Markman, A. B., & Makin, V. S. (1998). Referential communication and category acquisition.Journal of Experimental Psychology: General,127, 331–354.
Markman, A. B., & Ross, B. H. (in press). Category use and category learning.Psychological Bulletin.
Marks, L. E. (1989). On cross-modal similarity: The perceptual structure in pitch, loudness, and brightness.Journal of Experimental Psychology: Human Perception & Performance,15, 586–602.
Medin, D. L., Goldstone, R. L., & Gentner, D. (1993). Respects for similarity.Psychological Review,100, 254–278.
Medin, D. L., & Schaffer, M. M. (1978). Context theory of classification learning.Psychological Review,85, 207–238.
Norman, D. A., & Rumelhart, D. E. (1975).Explorations in cognition. San Francisco: Freeman.
Nosofsky, R. M., Gluck, M. A., Palmeri, T. J., McKinley, S. C., & Glauthier, P. (1994). Comparing models of rule-based classification learning: A replication and extension of Shepard, Hovland, and Jenkins (1961).Memory & Cognition,22, 352–369.
Nosofsky, R. M., Palmeri, T. J., & McKinley, S. C. (1994). Rule-plusexception model of classification learning.Psychological Review,101, 53–79.
Schank, R. C., Collins, G. C., & Hunter, L. E. (1986). Transcending inductive category formation in learning.Behavioral & Brain Sciences,9, 639–686.
Schyns, P. G., Goldstone, R. L., & Thibaut, J.-P. (1998). The development of features in object concepts.Behavioral & Brain Sciences,21, 1–54.
Shanon, B. (1988). The similarity of features.New Ideas in Psychology,6, 307–321.
Shepard, R. N., Hovland, C. L., & Jenkins, H. M. (1961). Learning and memorization of classifications.Psychological Monographs,75 (13, Whole No. 517).
Ullman, S. (1996).High-level vision. Cambridge, MA: MIT Press.
Wisniewski, E. J., & Medin, D. L. (1994). On the interaction of theory and data in concept learning.Cognitive Science,18, 221–281.
Yamauchi, T., Love, B. C., & Markman, A. B. (2002). Learning nonlinearly separable categories by inference and classification.Journal of Experimental Psychology: Learning, Memory, & Cognition,28, 585–593.
Yamauchi, T., & Markman, A. B. (1998). Category learning by inference and classification.Journal of Memory & Language,39, 124–149.
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This work was supported by AFOSR Grant F49620-01-1-0295 to B.C.L. and NSF Grant SBR-9905013 to A.B.M.
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Love, B.C., Markman, A.B. The nonindependence of stimulus properties in human category learning. Memory & Cognition 31, 790–799 (2003). https://doi.org/10.3758/BF03196117
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DOI: https://doi.org/10.3758/BF03196117