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Salvaging parts of the “classical theory” of categorization

Published online by Cambridge University Press:  04 February 2010

Dan Sperber
Dan Sperber
Affiliation:
Laboratorie d'ethnologie, C.N.R.S. and Université de Paris X, 9200 Nanterre, France1
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Information
Behavioral and Brain Sciences , Volume 9 , Issue 4 , December 1986 , pp. 668
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Copyright © Cambridge University Press 1986

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References

Abelson, R. (1981) Constraint, construal and cognitive science. In: The proceedings of Third Annual Conference of the Cognitive Science Society,Berkeley CA [rRCS]Google Scholar
Abbot, V., Black, J. & Smith, E. E. (1985) The representation of scripts in memory. Journal of Memory and Language 24:179–99. [EES]CrossRefGoogle Scholar
Anderson, J. R. (1983) The architecture of cognition. Harvard University Press. [JRA]Google Scholar
Anderson, J. R., Farrell, R. & Sauers, R. (1984) Learning to program in LISP. Cognitive Science 8:87–129. [JRA]Google Scholar
Anderson, J. R. & Kline, P. J. (1979) A learning system and its psychological implications. Proceedings of the Sixth International Joint Conference on Artificial Intelligence.Morgan-Kaufmann. [PL]Google Scholar
Anderson, J. R., Kline, P. J. & Beasley, C. M. (1979) A general learning theory and its application to schema abstraction. In: The psychology of learning and motivation, vol. 13, ed. Bower, G. H.. Academic Press. [arRCS, JRA]Google Scholar
Anderson, J. R. & Thompson, R. (1986) Use of analogy in a production system architecture. Presented at the University of Illinois Workshop on Similarity and Analogy. [JRA]Google Scholar
Angluin, D. (1981) A note on the number of queries needed to identify regular languages. Information and Control 51:76–87. [KTK]CrossRefGoogle Scholar
Angluin, D. & Smith, C. H. (1982) A survey of inductive inference: Theory and methods. Technical Report 250. Yale University. [KTK]Google Scholar
Armstrong, S., Gleitman, L. R. & Gleitman, H. (1981) What some concepts might not be. Cognition 13:263–308. [BL, GLM]CrossRefGoogle Scholar
Barsalou, L. W. (1982) Context-independent and context-dependent information in concepts. Memory and Cognition 10:82–93. [aRCS, LWB, JEC]CrossRefGoogle ScholarPubMed
Barsalou, L. W. (1983) Ad hoc categories. Memory and Cognition 11:211–27. [aRCS, LWB]CrossRefGoogle ScholarPubMed
Barsalou, L. W. (1985) Ideals, central tendency, and frequency of instantiation as determinants of graded structure in categories. Journal of Experimental Psychology: Learning, Memory, and Cognition 11:629–54. [rRCS, LWB, JEC, GLM, EES]Google ScholarPubMed
Barsalou, L. W. (1986) Intra-concept similarity and its implications for inter-concept similarity. To be presented at a conference on Similarity and Analogy at the University of Illinois in June (1986). Chapter in an edited volume to follow. [LWB]Google Scholar
Barsalou, L. W. (in press) The instability of graded structure: Implications for the nature of concepts. In: Concepts and conceptual development: Ecological and intellectual factors in categorization, ed. Neisser, U.. Cambridge University Press. [LWB]Google Scholar
Barsalou, L. W. & Medin, D. L. (1986) Concepts: Static definitions or context-dependent representations? Cahiers de Psychologie Cognitive. 6:187–202. [LWB]Google Scholar
Barsalou, L. W. & Ross, B. H. (1986) The roles of automatic and strategic processing in sensitivity to superordinate and property frequency. Journal of Experimental Psychology: Learning, Memory, and Cognition 12:116–34. [LWB]Google Scholar
Barsalou, L. W. & Sewell, D. R. (1984) Constructing representations of categories from different points of view. Emory Cognition Project Report no. 2. Emory University. [LWB]Google Scholar
Barsalou, L. W., Usher, J. A. & Sewell, D. R. (1985) Schema-based planning of events. Paper¯ presented at the Meeting of the Psychonomic Society, Boston. [LWB]Google Scholar
Bickhard, M. H. & Richie, D. M. (1983) On the nature of representation: A case study of James J. Gibson's theory of perception. Praeger. [RLC]Google Scholar
Birnbaum, L. (1985) A short note on opportunistic planning and memory for arguments. Proceedings of the Ninth International Joint Conference on Artificial Intelligence.Morgan-Kaufmann. [aRCS]Google Scholar
Bower, G. H., Black, J. B. & Turner, T. J. (1979) Scripts in memory for text. Cognitive Psychology 11:177–220. [aRCS]CrossRefGoogle Scholar
Brooks, L. R. (1978) Nonanalytic concept formation and memory for instances. In: Cognitive and categorization, ed. Rosch, E. & Lloyd, B. B.. Erlbaum. [aRCS, GLM]Google Scholar
Bruner, J. S., Goodnow, J. J. & Austin, G. A. (1956) A study of thinking. Wiley. [RLC]Google Scholar
Bruner, J. S., Goodnow, J. J. & Austin, G. A. (1956) A study of thinking. Science Editions. [arRCS]Google Scholar
Buchanan, B. G. & Mitchell, T. M. (1978) Model-based learning of production rules In: Pattern-directed inference systems, ed. Waterman, D. A. & Hayes-Roth, F.. Academic Press. [rRCS, TGD]Google Scholar
Bullock, M. (1985) Causal reasoning and developmental change in the preschool years. Human Development 28:169–91. [RLC]CrossRefGoogle Scholar
Bullock, M., Gelman, R. & Baillargeon, R. (1982) The development of causal reasoning. In: The developmental psychology of time, ed. Friedman, W. J.. Academic Press. [RLC]Google Scholar
Callanan, M. A. & Markman, E. M. (1982) Principles of organization in young children's natural language hierarchies. Child Development 53:1093–1101. [REP]Google Scholar
Campbell, R. L. & Bickhard, M. H. (1986a) Knowing levels and developmental stages. Karger. [RLC]Google Scholar
Campbell, R. L. & Bickhard, M. H. (1986b) Knowing levels and the development of natural kind categories. In: Interactivism and developmental psychology. Presented at Jean Piaget Society Symposium, Philadelphia. [RLC]Google Scholar
Campbell, R. L. & Bickhard, M. H. (in press) A deconstruction of Fodor's anticonstructivism. Human Development. [RLC]Google Scholar
Carbonell, J. G. (1985) Derivational analogy: A theory of reconstructive problem solving and expertise acquisition (Technical Report CMU-CS-85–115). Carnegie-Mellon University, Computer Science Department. [JRA]Google Scholar
Carbonell, J. G. (1986) Derivational analogy: A theory of reconstructive problem solving and expertise acquisition. In: Machine learning: An artificial intelligence approach, vol. 2, ed. Michalski, R. S., Carbonell, J. G. & Mitchell, T. M.. Morgan Kaufmann. [DK, mL]Google Scholar
Carey, S. (1985) Conceptual change in childhood. MIT Press. [GLM]Google Scholar
Chi, M. T. H., Feltovich, P. J. & Glaser, R. (1981) Categorization and representation of physics knowledge by experts and novices. Cognitive Science 5:121–52. [GLM]Google Scholar
Chomsky, N. (1957) Syntactic structures. Mouton. [REP]CrossRefGoogle Scholar
Chomsky, N. (1965) Aspects of the theory of syntax. MIT Press. [rRCS, EW]Google Scholar
Chomsky, N. (1975) Reflections on language. Pantheon. [EW]Google Scholar
Clark, E. V. (1983) Meanings and concepts. In: Manual of child psychology: Cognitive development, vol. 3, ed. Flavell, J. H. & Markman, E. M.. Wiley. [GLM]Google Scholar
Cohen, L. B. & Younger, B. A. (1983) Perceptual categorization in the infant. In: New trends in conceptual representation: Challenges to Piaget's theory? ed. Scholnick, E. K.. Erlbaum. [RLC]Google Scholar
Cohen, N. J. & Corkin, S. (1982) Learning to solve the Tower of Hanoi puzzle in amnesia. Presented at the Psychonomic Society, Minneapolis. [RLC]Google Scholar
Cullingford, R. (1978) “Script application: Computer understanding of newspaper stories.” Ph.D. thesis, Yale University. Research Report no. 116. [aRCS]Google Scholar
Dehn, N. (1981) Story generation after tale-spin. Proceedings of the Seventh International Joint Conference on Artificial Intelligence.Morgan-Kaufmann. [aRCS]Google Scholar
DeJong, G. (1981) Generalizations based on explanations. Proceedings of the Seventh International Joint Conference on Artificial Intelligence.Morgan-Kaufmann. [rRCS, DK]Google Scholar
DeJong, G. (1985) A brief overview of explanatory schema acquisition. Proceedings of the Third International Machine Learning Workshop, Skytop, Pa., 06. [rRCS]CrossRefGoogle Scholar
DeJong, G. F. (1986) An approach to learning from observation. In: Machine learning: An artificial intelligence approach, vol. 2, ed. Michalski, R. S., Carbonell, J. G. & Mitchell, T. M.. Morgan-Kaufmann. [mL]Google Scholar
DeJong, G. & Mooney, R. (in press) Explanation based learning: An alternative view. Machine Learning. [PL]Google Scholar
Dennett, D. C. (1978) Brainstorms. MIT Press. [rRCS]Google Scholar
Dietterich, T. G. (1980) Applying general induction methods to the card game Elusis. Proceedings of the National Conference on Artificial Intelligence. [aRCS]Google Scholar
Dietterich, T. G. & Michalski, R. S. (1981) Inductive learning of structural descriptions: Evaluation criteria and comparative review of selected methodologies. Artificial Intelligence 16:257–94. [aRCS]Google Scholar
Dietterich, T. & Michalski, R. (1983) A comparative review of selected methods of learning from examples. In: Machine learning, ed. Michalski, R., Carbonell, J. & Mitchell, T.. Morgan-Kaufmann. [YW]Google Scholar
Dunlaing, C. O. & Yap, C. (1982) The Voronoi diagram method of motion-planning I. Courant Institute of Mathematical Sciences. [DK]Google Scholar
Ellman, T. (1985) Generalizing logic circuit designs by analyzing proofs of correctness. Proceedings of the Ninth International Joint Conference on Artificial Intelligence.Morgan-Kaufmann. [ML]Google Scholar
Estes, W. K. (1986) Array models for category learning. Unpublished manuscript, Harvard University. [JEC]Google Scholar
Estes, W. K. (in press) Array models for category learning. Cognitive Psychology. [EES]Google Scholar
Estes, W. K., Burke, C. J., Atkinson, R. C. & Frankmann, J. P. (1957) Probabilistic discrimination learning. Journal of Experimental Psychology 54:233–39. [CPS]Google Scholar
Feldman, J. (1972) Some decidability results in grammatical inference. Information and Control 20:244–62. [KTK]CrossRefGoogle Scholar
Fodor, J. A. (1975) The language of thought Thomas Y. Crowell. [PT]Google Scholar
Fodor, J. A. (1981) Representations. MIT Press. [rRCS, RLC, BL]Google Scholar
Fodor, J. A. (1983) The modularity of mind. MIT Press. [aRCS, GLM, EES]Google Scholar
Fodor, J. A., Fodor, J. D. & Garrett, M. (1975) The psychological unreality of semantic representations. Linguistic Inquiry 6:515–31. [DS]Google Scholar
Fried, L. & Holyoak, K. (1984) Induction of category distributions: A framework for classification learning. Journal of Experimental Psychology: Learning, Memory, and Cognition 10:234–57. [aRCS, JEC]Google Scholar
Garey, M. R. and Johnson, D. S. (1979) Computers and intractability: A guide to the theory of NP-Completeness, W. H. Freeman. [DK]Google Scholar
Gelman, S. A., Collman, P. & Maccoby, E. E. (1986) Inferring properties from categories versus inferring categories from properties: The case of gender. Child Development 57:396–404. [RLC]Google Scholar
Gentner, D. (1983) Structure-mapping: A theoretical framework for analogy. Cognitive Science, 7/2:150–70. [DK]Google Scholar
Gleitman, L. & Wanner, E. (1982) Language acquisition: The state of the state of the art. In: Language acquisition: The state of the art, ed. Wanner, E. & Gleitman, L.. Cambridge University Press. [EW]Google Scholar
Gold, E. M. (1967) Language identification in the limit. Information and Control 10:447–74. [arRCS, KTK]Google Scholar
Gold, E. M. (1978) Complexity of automaton identification from given data. Information and Control 10:447–74. [KTK]Google Scholar
Goodman, N. (1979) Fact, fiction, and forecast. Hachett. [BL]Google Scholar
Hanson, N. R. (1958). Patterns of discovery. Cambridge University Press. [CPS]Google Scholar
Hanson, S. & Bauer, M. (1986) Machine learning clustering and polymorphy. In: Approaches to uncertainty in AI, ed. Kanal, L. & Lemmer, J.. North Holland. [SJH]Google Scholar
Harman, G. (1973) Thought. Princeton University Press. [JTT]Google Scholar
Harnad, S. (Ed.) (1987) Categorical perception. Cambridge University Press. [REP]Google Scholar
Harré, R. (1970) The principles of scientific thinking. University of Chicago Press. [RLC]CrossRefGoogle Scholar
Harré, R. & Madden, E. H. (1975) Causal powers. Rowman and Littlefield. [RLC]Google Scholar
Hasher, L. & Zacks, R. T. (1979) Automatic and effortful processes in memory. Journal of Experimental Psychology: General 108:356–88. [RLC]CrossRefGoogle Scholar
Hayes-Roth, F. & McDermott, J. (1977) Knowledge acquisition from structure descriptions. Proceedings of the Fifth International Joint Conference on Artificial Intelligence.Morgan-Kaufmann. [aRCS]Google Scholar
Holland, J., Holyoak, K., Nisbett, R. & Thagard, P. (1986) Induction: Processes of inference, learning, and discovery. MIT Press. [rRCS, PT]Google Scholar
Horning, J. J. (1969) A study of grammatical inference. Ph.D. thesis, Stanford University, Computer Science Dept. [KTK]Google Scholar
Hunt, E. B. (1962) Concept learning: An information processing problem. Wiley. [aRCS]Google Scholar
Hunt, E. B., Marin, J. & Stone, P. (1966) Experiments in induction. Academic Press. [CG]Google Scholar
Jacoby, L. L. & Brooks, L. R. (1984) Nonanalytic cognition: Memory, perception, and concept learning. In: The psychology of learning and motivation: Advances in research and theory, vol. 18, ed. Bower, G. H.. Academic Press. [LWB]Google Scholar
Jusczyk, P. W. (1981) Infant speech perception: A critical appraisal. In: Perspectives in the study of speech, ed. Eimas, P. D. & Miller, J. L.. Erlbaum. [REP]Google Scholar
Kahneman, D. & Miller, D. T. (1986) Norm theory: Comparing reality to its alternatives. Psychological Review 93:136–53. [LWB]Google Scholar
Kass, A. (1986) Modifying explanations to understand stories. Proceedings of the Eighth Annual Conference of the Cognitive Science Society.Cognitive Science Society. [rRCS]Google Scholar
Katz, J. J. (1981) Language and other abstract objects. Rowman and Littlefield. [DS]Google Scholar
Keil, F. C. (1981) Constraints on knowledge and cognitive development. Psychological Review 88:197–227. [aRCS]Google Scholar
Keil, F. C. (1986) The acquisition of natural kind and artifact terms. In: Language learning and concept acquisition: foundation issues, ed. Demopoulos, W. & Marras, A.. Ablex. [RLC]Google Scholar
Kyburg, H. E. Jr. (1983) Rational belief. Brain and Behavioral Sciences 6:231–75. [HEK]Google Scholar
LaBerge, D. (1976) Perceptual learning and attention. In: Handbook of learning and cognitive processes, vol. 4, ed. Estes, W. K.. Erlbaum. [aRCS]Google Scholar
Landau, B. & Gleitman, L. (1985) Language and experience. Harvard University Press. [EW]Google Scholar
Langley, P. (1982) Language acquisition through error recovery. Cognition and Brain Theory 5:211–55. [PL]Google Scholar
Larkin, J. H. (1985) Understanding problem representations, and skill in physics. In: Thinking and learning skills, vol. 2: Research and open questions, ed. Chipman, S. F., Segal, J. W. & Glaser, R.. Erlbaum. [GLM]Google Scholar
Leake, D. & Owens, C. (1986) Organizing memory for explanation. Proceedings of the Eighth Annual Conference of the Cognitive Science Society.Cognitive Science Society. [rRCS]Google Scholar
Lebowitz, M. (1980) Generalization and memory in an integrated understanding system. (Tech. Rep. No. 186). Yale University Department of Computer Science. [ML]Google Scholar
Lebowitz, M. (1982) Correcting erroneous generalizations. Cognition and Brain Theory 5:367–81. [ML, PL]Google Scholar
Lebowitz, M. (1983) Generalization from natural language text. Cognitive Science 7:1–40. [ML]Google Scholar
Lebowitz, M. (1986a) Integrated learning: Controlling explanation. Cognitive Science 10:219–40. [ML]Google Scholar
Lebowitz, M. (1986b) Not the path to perdition: The utility of similarity-based learning. Columbia University Department of Computer Science. [ML]Google Scholar
Lebowitz, M. (1986c) Concept learning in a rich input domain: Generalization-based Memory. In: Machine learning: An artificial intelligence approach, vol. 2. ed. Michalski, R. S., Carbonell, J. G. & Mitchell, T. M.. Morgan Kaufmann. [ML]Google Scholar
Lindsay, R., Buchanan, B., Feigenbaum, E. & Lederberg, J. (1980) Applications of artificial intelligence for organic chemistry. McGraw Hill. [CG]Google Scholar
Lycan, W. G.Conservatism and the data base. Manuscript. [JTT]Google Scholar
McClelland, J. L. & Rumelhart, D. E., eds. (1985) Distributed memory and the representation of general and specific information. Journal of Experimental Psychology 114:159–88. [rRCS, JRA]Google Scholar
McDermott, D. V. (1981) Artificial intelligence meets natural stupidity. In: Pattern directed inference systems, ed. Haugeland, J.. MIT Press. [rRCS]Google Scholar
McFadden, R. (1986) Two bottles of poisoned tylenol were shipped by the same distributor. New fork Times 135:1. [ML]Google Scholar
McGuire, R., Birnbaum, L. & Flowers, M. (1981) Opportunistic processing in arguments. Proceedings of the Seventh International Joint Conference on Artificial Intelligence.Morgan-Kaufmann. [aRCS]Google Scholar
Medin, D. L. (1982) Structural principles of categorization. In: Perception, development, and cognition: An interactional approach, ed. Shepp, B. & Tighe, T.. Erlbaum. [JEC]Google Scholar
Medin, D. L. & Schaeffer, M. M. (1978) A context theory of classification learning. Psychological Review 85:207–38. [rRCS, JRA, GLm]Google Scholar
Menzel, E. M. (1978) Cognitive mapping in chimpanzees. In: Cognitive processes in animal behavior, ed. Hulse, S. H., Fowler, H. & Honig, W. K.. Erlbaum. [CPS]Google Scholar
Michalski, R. S. (1980) Pattern recognition as rule-guided inductive inference. IEEE Transactions on Pattern Analysis and Machine Intelligence 24:349–61. [aRCS]Google Scholar
Michalski, R. S. (1983) Theories and methodology of inductive learning. Artificial Intelligence 20/2:111–61. [arRCS]Google Scholar
Michalski, R. S., Carbonell, J., Anderson, J. & Mitchell, T. (1983) Machine learning: An artificial intelligence approach. Tioga Press. [CG]Google Scholar
Michalski, R. S. & Larson, J. B. (1978) Selection of most representative training examples and incremental addition of VL1 hypothesis: The underlying methodology and the description of programs ESEL and AQ11. Technical Report no. 867, Computer Science Department, University of Illinois. [aRCS]Google Scholar
Michalski, R. S. & Stepp, R. (1983) Learning from observation: Conceptual clustering. In: Machine learning: An artificial intelligence approach, ed. Michalski, R. S., Carbonell, J. G. & Mitchell, T. M.. Tioga Press. [rRCS, PL]Google Scholar
Millikan, R. G. (1984) Language, thought, and other biological categories, Chapters 16 & 17. MIT Press. [RGM]Google Scholar
Minsky, M. (1961) Steps toward artificial intelligence. Proceedings of the Institute of Radio Engineers 49:8–30. Reprinted in E. Feigenbaum & J. Feldman (1963) Computers and thought. McGraw-Hill. [arRCS]Google Scholar
Minsky, M. (June (1979)) K-lines: A theory of memory. MIT AI memo, no. 516. [DK] (forthcoming) Society of mind. Simon and Schuster. [DK]Google Scholar
Mitchell, T. M. (1978) “Version spaces: An approach to concept learning.” Ph.D. Thesis. Stanford University. [aRCS]Google Scholar
Mitchell, T. M. (1979) An analysis of generalization as a search problem. Proceedings of the Sixth International Joint Conference on Artificial Intelligence.Morgan-Kaufmann. [aRCS]Google Scholar
Mitchell, T. M. (1983) Learning and problem solving. Proceedings of the Eighth International Joint Conference on Artificial Intelligence.Morgan-Kaufmann. [aRCS, ML, YW]Google Scholar
Mitchell, T. M., Keller, R. M. & Kedar-Cabelli, S. T. (1986) Explanation-based generalization: A unifying view. Machine Learning 1:47–80. [rRCS, JRA, DK, PL]Google Scholar
Mitchell, T. M., Utgoff, P. E., Nudel, B. & Banerji, R. B. (1981) Learning problem-solving heuristics through practice. Proceedings of the Seventh International Joint Conference on Artificial Intelligence.Morgan-Kaufmann. [aRCS]Google Scholar
Mostow, J. (1983) Operationalizing advice: A problem-solving model. Proceedings of the (1983) International Machine Learning Workshop, Champaign-Urbana, Illinois. [ML]Google Scholar
Murphy, G. L. & Medin, D. L. (1985) The role of theories in conceptual coherence. Psychological Review 92:289–316. [arRCS, LWB, JEC, GLM, CPS]Google Scholar
Murphy, G. L. & Wright, J. C. (1984) Changes in conceptual structure with expertise: Differences between real-world experts and novices. Journal of Experimental Psychology: Learning, Memory, and Cognition 10:144–55. [GLM]Google Scholar
Nelson, D. G. K. (1984) The effect of intention on what concepts are acquired. Journal of Verbal Learning and Verbal Behavior 23:734–59. [EES]Google Scholar
Newell, A. (1969) Heuristic programming: Ill-structured problems. In: Progress in operations research, ed. Amofsky, J.. Wiley. [TGD]Google Scholar
Nicod, J. (1970) Geometry and induction: Containing geometry in the sensible world and the logical problem of induction, trans. Bell, J. & Wood, M.. University of California Press. [HEK]Google Scholar
Osherson, D. N. & Smith, E. E. (1981) On the adequacy of prototype theory as a theory of concepts. Cognition 9:35–58. [GLM]Google Scholar
Pao, T. W. & Carr, J. W. III (1978) A solution of the syntactical induction-inference problem for regular languages. Computer Languages 3:53–64. [KTK]CrossRefGoogle Scholar
Pazzani, M. J. (1985) Explanation and generalization based memory. (Technical Report no. UCLA-AI-85–13). UCLA Artificial Intelligence Laboratory. [ML]Google Scholar
Piaget, J. (1977) Essai sur la nécessité. Archives de Psychologie 45:235–51. (English trans., in press, Human Development). [RLC]Google Scholar
Pitt, L. (1984) A characterization of probabilistic inference. Ph. D. thesis, Yale University, Computer Science Department. [KTK]Google Scholar
Pomerantz, J. R., Sager, L. C. & Stoever, R. G. (1977) Perception of wholes and their component parts: Some configurai superiority effects. Journal of Experimental Psychology: Human Perception and Performance 3:422–35. [REP]Google Scholar
Pople, H. E. (1975) On the mechanization of abductive logic. Proceedings of the Fourth international Joint Conference on Artificial Intelligence.Morgan-Kaufmann. [aRCS]Google Scholar
Popper, K. (1965) Conjectures and refutations. Harper. [RLC]Google Scholar
Posner, M. I. (1980) Orienting of attention. Quarterly Journal of Experimental Psychology 32:3–25. [DK]Google Scholar
Posner, M. I. & Kelle, S. W. (1968) On the genesis of abstract ideas. Journal of Experimental Psychology 77:353–63. [RLC, GLM]Google Scholar
Putnam, H. (1975) The meaning of “meaning.” In: Mind language and reality: Philosophical papers, vol. 2. Cambridge University Press. [RLC]Google Scholar
Quine, W. V. (1960) Word and object. MIT Press. [rRCS, BL]Google Scholar
Quine, W. V. & Ullian, J. S. (1973) The web of belief. Random House. [JTT]Google Scholar
Reed, S. K. (1972) Pattern recognition and categorization. Cognitive Psychology 3:382–407. [GLM]Google Scholar
Repp, B. H. (1983) Trading relations among acoustic cues in speech perception are largely a result of phonetic categorization. Speech Communication 2:341–62. [REP]Google Scholar
Rosch, E. & Mervis, C. B. (1975) Family resemblances: Studies in the internal structure of categories. Cognitive Psychology 7:573–605. [aRCS, JEC, GLM]Google Scholar
Roth, E. M. & Shoben, E. J. (1984). The effect of context on the structure of categories. Cognitive Psychology 15:346–78. [LWB]Google Scholar
Schank, R. C. (1982) Dynamic memory: A theory of learning in computers and people. Cambridge University Press [arRCS, CG, KTK, ML]Google Scholar
Schank, R. C. (1984) Explanation: A first pass. Technical Report no. 330. Yale University. [arRCS]Google Scholar
Schank, R. C. (in press) Explanation patterns: Understanding mechanically and creatively. Erlbaum. [rRCS]Google Scholar
Schank, R. C. & Abelson, R. (1977) Scripts, plans, goals and understanding. Erlbaum. [aRCS]Google Scholar
Schank, R. C. & Riesbeck, C. (1985) Explanation: A second pass. Technical Report no. 384. Department of Computer Science, Yale University. [arRCS]Google Scholar
Schneider, W. & Sniffrin, R. M. (1977) Controlled and automatic human information processing: 1. Detecting, search, and attention. Psychological Review 84:1–66. [EES]Google Scholar
Shapiro, E. (1980) Inductive inference of theories from facts. Ph.D. thesis, Yale University, Computer Science Department. [KTK]Google Scholar
Shimp, C. P. (1973) Probabilistic discrimination learning in the pigeon. Journal of Experimental Psychology 97:292–304. [CPS]CrossRefGoogle Scholar
Shimp, C. P. (1984a) Timing, learning, and forgetting. In: Timing and perception, ed. Gibbon, J. & Allan, L.. New York Academy of Sciences. [CPS]Google Scholar
Shimp, C. P. (1984b) Relations between memory and operant behavior, according to an associative learner (AL). Canadian Journal of Psychology 38:269–84. [CPS]Google Scholar
Shimp, C. P. (1984c) Cognition, behavior, and the experimental analysis of behavior. Journal of the Experimental Analysis of Behavior 42:407–20. [CPS]Google Scholar
Shimp, C. P. (1984d) The question: Not shall it be, but which shall it be? Commentary on “Are theories of learning necessary?” by B. F. Skinner. Behavioral and Brain Sciences 7:536–37. [CPS]Google Scholar
Shultz, T. R. (1982) Rules of causal attribution. Monographs of the Society for Research in Child Development 47:(1, ser. no. 194). [RLC]Google Scholar
Silver, B. (1986) Precondition analysis: Learning control information. In: Machine learning: An artificial intelligence approach, vol. 2, ed. Michalski, R. S., Carbonell, J. G. & Mitchell, T. M.. Morgan-Kaufmann. [ML]Google Scholar
Simon, C. & Fourcin, A. J. (1978) Cross language study of speech pattern learning. Journal of the Acoustical Society of America 63:925–35. [REP]Google Scholar
Skinner, B. F. (1984) Theoretical contingencies. Behavioral and Brain Sciences 7:544. [CPS]Google Scholar
Smith, A. H. (1963) The mushroom hunter's field guide. University of Michigan Press. [HER]Google Scholar
Smith, E. E. (1978) Theories of semantic memory. In: Handbook of learning and cognitive processes, vol. 6, ed. Estes, W. K.. Erlbaum. [GLM]Google Scholar
Smith, E. E. & Medin, D. L. (1981) Categories and concepts. Harvard University Press. [aRCS, GLM, EES]Google Scholar
Soames, S. (1985) Semantics and psychology. In: The philosophy of linguistics, ed. Katz, J. J.. Oxford University Press. [DS]Google Scholar
Sperber, D. & Wilson, D. (1986) Relevance: Communication and cognition. Harvard University Press. [DS]Google Scholar
Spence, K. W. (1942) The basis of solution by chimpanzees of the intermediate size problem. Journal of Experimental Psychology 31:257–71. [CPS]Google Scholar
Tolman, E. C. & Brunswick, E. (1935) The organism and the causal texture of the environment. Psychological Review 42:43–77. [CPS]Google Scholar
Treisman, A. & Gelade, G. (1980) A feature-integration theory of attention. Cognitioe Psychology 12:97–136. [DK, REP]Google Scholar
Treisman, A. & Patterson, R. (1984) Emergent features, attention, and object perception. Journal of Experimental Psychology: Human Perception and Performance 10:12–31. [REP]Google Scholar
Tversky, A. (1977) Features of similarity. Psychological Review 84:327–52. [JEC]Google Scholar
Tversky, A. & Kahneman, D. (1974) Judgement under uncertainty: Heuristics and biases. Science 185:1124–31. [SJH]Google Scholar
Ullman, S. (1983) Visual routines. MIT AI memo, no. 723. [DK]Google Scholar
VanLehn, K. (1983) Human procedural skill acquisition: Theory, model, and psychological validation. Proceedings of the national conference on artificial intelligence.Morgan-Kaufmann. [TGD]Google Scholar
Vere, S. A. (1978) Inductive learning of relational productions. In: Pattern directed inference systems, ed. Waterman, D. A. & Hayes-Roth, F.. Academic Press. [aRCS]Google Scholar
Von Wright, G. H. (1960) A treatise on induction and probability. Littlefield, Adams. [HEK]Google Scholar
Wagner, A. R. (1976) Priming in STM: An information-processing mechanism for self-generated or retrieval-generated depression in performance. In: Habituation, ed. Tighe, T. J. & Leaton, R. N.. Erlbaum. [CPS]Google Scholar
Waterman, D. A. (1970) Generalization learning techniques for automating the learning of heuristics. Artificial Intelligence 1:121–70. [aRCS]Google Scholar
Wexler, K. & Culicover, P. (1980) Formal principles of language acquisition. MIT Press. [KTK]Google Scholar
Winston, P. H. (1970) Learning structural descriptions from examples. AI Laboratory, Massachusetts Institute of Technology, Technical Report no. 231. Reprinted (1975) in: The psychology of computer vision, ed. P. H. Winston. McGraw-Hill. [aRCS, PL]Google Scholar
Winston, P. & Horn, B. (1975) The psychology of computer vision. McGraw-Hill. [CG]Google Scholar
Winston, P. & Horn, B. (1977) Artificial intelligence. Addison-Wesley. [aRCS]Google Scholar
Winston, P. H. (1980) Learning and reasoning by analogy. In: Communications of Association for Computing Machinery vol. 23, no. 12. [DK]Google Scholar
Winston, P. H., Binford, T. O., Katz, B. & Lowry, M. (1983) Learning physical descriptions from functional definitions, examples, and precedents. Massachusetts Institute of Technology AI memo, no. 679. [DK]Google Scholar
Winston, P. H., Binford, T. O., Katz, B. & Lowry, M. (1983) Learning physical descriptions from function definitions, examples, and precedents. Proceedings of the National Conference on Artificial Intelligence.Morgan-Kaufmann. [aRCS, JRA, ML]Google Scholar
Witkin, A. (1983) Scale-space filtering. Proceedings of the Eighth International Joint Conference for Artificial Intelligence. [DK]Google Scholar
Wittgenstein, L. (1953) Philosophical investigations, 3rd edition, trans. Anscombe, G. E. M.. MacMillan. [aRCS, CPS]Google Scholar