Concepts and Similarity

Knowledge, Concepts and Categories

Volumn , Issue , 2024, Pages 43-92

  Hahn, Ulrike ^a   Chater, Nick ^a  

^a UNIVERSITY OF WARWICK   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 85211858633     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.4324/9781003575344-3     Document Type: Chapter

References (127)

1. AAAI 1993. Proceedings of the AAAI-93 Workshop on Case-Based Reasoning. AAAI Press.
2. Allen, S. & L. Brooks 1991. Specializing the operation of an explicit rule. Journal of Experimental Psychology: General 120, 3-19.
3. Ashley, K. 1990. Modeling legal argument-reasoning with cases andhypotheticals. Cambridge, Mass.: MIT press.
4. Bareiss, R. & J. King 1989. Similarity assessment and case-based reasoning. In Proceedings: Case-Based Reasoning Workshop, 67-71. San Mateo, California: Morgan Kaufmann.
5. Barsalou, L. 1982. Context-independent and context-dependent information inconcepts. Memory and Cognition 10, 82-93.
6. Barsalou, L. 1983. Ad hoc categories. Memory and Cognition 11, 211-27.
7. Barsalou, L. 1987. The instability of graded structure: implications for thenature of concepts In Concepts and conceptual development: ecological andintellectual factors in categorization, U. Neisser (ed.), 101-140. Cambridge:Cambridge University Press.
8. Bayer, M., B. Harbig S. Wess 1992. Ahnlichkeit und Ahnlichkeitsmasse InFallbasiertes Schliessen: eine Ubersicht. Techreport: SEKI Working PaperSWP-92-08.
9. Bechtel, W. & A. Abrahamsen 1991. Connectionism and the mind. Oxford:Blackwell.
10. Branting, K. 1991. Integrating rules and precedents for classification andexplanation. PhD thesis, University of Texas, Austin.
11. Brooks, L. 1978. Nonanalytic concept formation and memory for instances. In Cognition and categorization, E. Rosch & B. Lloyd (eds), 169-211. Hillsdale, New Jersey: Erlbaum.
12. Bruner, J., J. Goodnow, G. Austin 1956. A study of thinking. New York: JohnWiley.
13. Carey, S. 1985. Conceptual change in childhood. Cambridge, Mass.: BradfordBooks.
14. Chaitin, G. 1987. Algorithmic information theory. Cambridge: CambridgeUniversity Press.
15. Chater, N. & M. Oaksford 1990. Autonomy, implementation, and cognitivearchitecture: a reply to Fodor and Pylyshyn. Cognition 34, 93-107.
16. Chater, N. & M. Oaksford 1993. Logicism, mental models and everydayreasoning: reply to Garnham. Mind and Language 8, 72-89.
17. Choi, S., M. McDaniel J. Busemeyer 1993. Incorporating prior biases in networkmodels of conceptual rule learning. Memory and Cognition 21, 413-23.
18. Christiansen, M. & N. Chater 1997. Connectionism and natural languageprocessing. In Language processing, S. Garrod & M. Pickering (eds). London:UCL Press.
19. Churchland, P. S. & T. J. Sejnowski 1992. The computational brain. Cambridge, Mass.: MIT Press.
20. Collins, A. & M. Quillian 1972. Experiments on semantic memory and languagecomprehension. In Cognition in learning and memory, L. Gregg (ed.). NewYork: John Wiley.
21. Coltheart, M., B. Curtis, P. Atkins M. Haller 1993. Models of reading aloud: dual-route and parallel-distributed processing approaches. Psychological Review 100, 589-608.
22. Cost, S. & S. Salzberg 1993. A weighted nearest neighbour algorithm forlearning with symbolic features. Machine Learning 10, 57-78.
23. DARPA 1989. Machine learning program plan: case-based reasoning. In Proceedings: Case-based Reasoning Workshop, 1-14. San Mateo, California:Morgan Kaufmann.
24. Fodor, J. 1975. The language of thought. New York: Cromwell.
25. Fodor, J., M. Garrett, E. Walker C. Parkes 1980. Against definitions. Cognition 8, 1-105.
26. Fodor, J. & E. Lepore 1992. Paul Churchland: State space semantics. In Holism:a shoppers guide. Oxford: Blackwell.
27. Fodor, J. & B. McLaughlin 1990. Connectionism and the problem ofsystematicity: why Smolensky’s solution won’t work. Cognition 35, 13-204.
28. Fodor, J. & Pylyshyn, Z. 1988. Connectionism and cognitive architecture: acritical analysis. Cognition 28, 3-71.
29. Garner, W. 1978. Aspects of a stimulus: features, dimensions, and configurations. In Cognition and categorization, E. Rosch, B. & Lloyd (eds), Hillsdale, NewJersey: Lawrence Erlbaum.
30. Gati, I. & A. Tversky 1982. Representations of qualitative and quantitativedimensions. Journal of Experimental Psychology: Human Perception andPerformance 8, 325-40.
31. Gati, I. & A. Tversky 1984. Weighting common and distinctive features inperceptual and conceptual judgements. Cognitive Psychology 16, 341-70.
32. Gentner, D. 1983. Structure-mapping: a theoretical framework for analogy Cognitive Science 7, 155-70.
33. Gluck, M. 1991. Stimulus generalization and representation in adaptive networkmodels of category learning. Psychological Science 2, 50-55.
34. Goldstone, R. 1994a. The role of similarity in categorization: providing agroundwork. Cognition 52, 125-57.
35. Goldstone, R. 1994b. Similarity, interactive activation, and mapping. Journalof Experimental Psychology: Learning, Memory, and Cognition 20, 3-28.
36. Goldstone, R., D. Medin, D. Gentner 1991. Relational similarity and thenonindependence of features in similarity judgements. Cognitive Psychology 23, 222-62.
37. Goodman, N. 1972. Problems and projects. Indianapolis: Bobbs Merill.
38. Hadley, R. 1994. Systematicity in connectionist language learning. Mind andLanguage 9, 247-72.
39. Hahn, U. & N. Chater 1996. Understanding similarity: a joint project forpsychology, case-based reasoning, and law. Artificial Intelligence Review, inpress.
40. Hinton, G. 1986. Learning distributed representations of concepts. In Proceedings of the Eighth Annual Meeting of the Cognitive Science Society. Hillsdale, New Jersey: Erlbaum.
41. Hintzman, D. & G. Ludlam 1980. Differential forgetting of prototypes and oldinstances: simulation by an exemplar-based classification model. Memory andCognition 8, 378-82.
42. Homa, D., S. Sterling, L. Trepel 1981. Limitations of exemplar-basedgeneralization and the abstraction of categorical information. Journal ofExperimental Psychology: Learning, Memory, and Cognition 7, 418-39.
43. Hunt, E., J. Marin, P. Stone 1966. Experiments in induction. New York: AcademicPress.
44. Jones, C. & E. Heit 1993. An evaluation of the total similarity principle. Journal of Experimental Psychology: Learning, Memory, and Cognition 19, 799-812.
45. Keil, F. 1989. Concepts, kinds and development. Cambridge, Mass.: Bradford Books.
46. Kolodner, J. 1992. An introduction to case-based reasoning. Artificial Intelligence Review 6, 3-34.
47. Komatsu, L. 1992. Recent views of conceptual structure. Psychological Bulletin 112, 500-526.
48. Kruschke, J. 1992. alcove: An exemplar-based connectionist model of category learning. Psychological Review 99, 22-44.
49. Lakoff, G. 1987. Cognitive models and prototype theory. In Concepts and conceptual development: ecological and intellectual factors in categorization, U. Neisser (ed.), 63-100. Cambridge: Cambridge University Press.
50. Lamberts, K. 1994. Flexible tuning of similarity in exemplar-based categorization. Journal of Experimental Psychology: Learning, Memory, and Cognition 20, 1003-1021.
51. Lamberts, K. 1995. Categorization under time pressure. Journal of Experimental Psychology: General 124, 161-80.
52. Levine, M. 1975. A cognitive theory of learning: research on hypothesis testing. Hillsdale, New Jersey: Erlbaum.
53. Li, M. & P. Vitanyi 1993. An introduction to Kolmogorov complexity and its applications. New York: Springer.
54. Marr, D. 1982. Vision. San Francisco: W. H. Freeman.
55. McClelland, J. & J. Elman 1986. Interactive processes in speech perception: the trace model. In Parallel distributed processing, vol. 2: psychological and biological models, D. Rumelhart & J. McClelland (eds), 58-121. Cambridge, Mass.: MIT press.
56. McClelland, J. & D. Rumelhart 1981. An interactive activation model of context effects in letter perception, part 1: an account of basic findings. Psychological Review 88, 375-407.
57. McClelland, J., D. Rumelhart, G. Hinton 1986. Parallel distributed processing-explorations in the microstructure of cognition. Cambridge, Mass.: MITpress.
58. McRae, K., V. de Sa, M. Seidenberg, 1993. Modeling property intercorrelations in conceptual memory. In Proceedings of the Annual Meeting of the Cognitive Science Society, 729-34. Boulder, Colorado: Cognitive Science Society.
59. Medin, D. 1989. Concepts and conceptual structure. American Psychologist 44, 1469-1481.
60. Medin, D. L. & W. Wattenmaker 1987. Category cohesiveness, theories, and cognitive archaeology. In Concepts and conceptual development: Ecological and intellectual factors in categorization, U. Neisser (ed.), 25-62. Cambridge: Cambridge University Press.
61. Medin, D., G. Dewey, T. Murphy 1983. Relationships between item and category learning: Evidence that abstraction is not automatic. Journal of Experimental Psychology: Learning, Memory, and Cognition 9, 607-625.
62. Medin, D., R. Goldstone, D. Gentner 1993. Respects for Similarity. Psychological Review 100, 254-78.
63. Medin, D. & M. Schaffer 1978. Context theory of classification learning. Psychological Review 85, 207-238.
64. Miller, G. & P. Johnson-Laird 1976. Language and perception. Cambridge, Mass.: Harvard University Press.
65. Minsky, M. 1977. Frame theory. In Thinking: readings in cognitive science, P. Johnson-Laird & P. Wason (eds). Cambridge: Cambridge University Press.
66. Murphy, G. & D. Medin 1985. The role of theories in conceptual coherence. Psychological Review 92, 289-316.
67. Neisser, U. 1987. From direct perception to conceptual structure. In Conceptsand conceptual development: ecological and intellectual factors incategorization, U. Neisser (ed.), 1-20. Cambridge: Cambridge University Press.
68. Neisser, U. & P. Weene 1962. Hierarchies in concept attainment. Journal ofExperimental Psychology 64, 640-45.
69. Nosofsky, R. 1984. Choice, similarity and the context theory of classification. Journal of Experimental Psychology: Learning, Memory, and Cognition 10, 104-114.
70. Nosofsky, R. 1988. Exemplar-based accounts of relations between classification, recognition, and typicality. Journal of Experimental Psychology: Learning, Memory, and Cognition 14, 700-708.
71. Nosofsky, R. 1990. Relations between exemplar-similarity and likelihood modelsof classification. Journal of Mathematical Psychology 34, 812-35.
72. Nosofsky, R. 1991. Stimulus bias, asymmetric similarity, and classification. Cognitive Psychology 23, 94-140.
73. Nosofsky, R., S. Clark, H. Shin 1989. Rules and exemplars in categorization, identification, and recognition. Journal of Experimental Psychology:Learning, Memory, and Cognition 15, 282-304.
74. Oaksford, M. & N. Chater 1991. Against logicist cognitive science. Mind andLanguage 6, 1-38.
75. Oden, G. C. 1987. Concept, knowledge, and thought. Annual Review ofPsychology 38, 203-237.
76. Osherson, D. & E. Smith 1981. On the adequacy of prototype theory as a theoryof concepts. Cognition 9, 35-58.
77. Pinker, S. & A. Prince 1988. On language and connectionism: Analysis of aparallel distributed processing model of language acquisition. Cognition 28, 73-193.
78. Plunkett, K. & V. Marchman 1991. U-shaped learning and frequency effects ina multi-layered perceptron: Implications for child language acquisition. Cognition 38, 43-102.
79. Pollack, J. 1990. Recursive distributed representations. Artificial Intelligence 46, 77-105.
80. Porter, B., R. Bareiss, R. Holte 1990. Concept learning and heuristicclassification. Artificial Intelligence 45, 229-63.
81. Posner, M. & S. Keele 1970. Retention of abstract ideas. Journal of ExperimentalPsychology 83, 304-308.
82. Pylyshyn, Z. 1973. What the mind’s eye tells the mind’s brain: A critique ofmental imagery. Psychological Bulletin 80, 1-24.
83. Restle, F. 1962. The selection of strategies in cue learning. Psychological Review 69, 329-43.
84. Richter, M., S. Wess, K. Althoff, F. Maurer 1993. Presentations and posters atthe First European Workshop on Case-based Reasoning. SEKI ReportSR-93-12 (SFB 314).
85. Riesbeck, C. & R. Schank 1989. Inside case-based reasoning. Hillsdale, NewJersey: Erlbaum.
86. Rips, L. 1989. Similarity, typicality and categorization. In Similarity andanalogical reasoning, S. Vosniadou & A. Ortony (eds), 21-59. Cambridge:Cambridge University Press.
87. Rips, L. & A. Collins 1993. Categories and resemblance. Journal of ExperimentalPsychology: General 122, 468-86.
88. Rissanen, J. 1989. Stochastic complexity in statistical inquiry. New Jersey: WorldScientific.
89. Rosch, E. 1975. Cognitive reference points. Cognitive Psychology 7, 532-47.
90. Rosch, E. 1978. Principles of categorization. In Cognition and categorization, E. Rosch & B. Lloyd (eds). Hillsdale, New Jersey: Erlbaum.
91. Rosch, E., C. Mervis, W. Gray, D. Johnson P. Boyes-Braem 1976. Basic objectsin natural categories. Cognitive Psychology 8, 382-439.
92. Roscheisen, M., R. Hofman, V. Tresp 1992. Neural controlling for rolling mills:incorporating domain theories to overcome data deficiency. Advances inNeural Information Processing 4. San Mateo, California: Morgan Kaufman.
93. Ross, B. 1984. Remindings and their effects in learning a cognitive skill. Cognitive Psychology 16, 371-416.
94. Ross, B. 1987. This is like that: The use of earlier problems and the separationof similarity effects. Journal of Experimental Psychology: Learning, Memory, and Cognition 13, 629-37.
95. Ross, B. 1989. Some psychological results on case-based reasoning. In Proceedings of the Workshop on Case-based Reasoning, San Mateo, CA:Morgan Kaufmann.
96. Ross, B. & P. Kennedy 1990. Generalizing from the use of earlier exemplars inproblem solving. Journal of Experimental Psychology: Learning, Memory, andCognition 16, 42-55.
97. Ross, B., S. Perkins, P. Tenpenny 1990. Reminding-based category learning. Cognitive Psychology 22, 460-92.
98. Roth, E. & E. Shoben 1983. The effect of context on the structure of categories. Cognitive Psychology 15, 346-78.
99. Rumelhart, D. & J. McClelland 1985. Distributed memory and therepresentation of general and specific information. Journal of ExperimentalPsychology: General 114, 159-88.
100. Rumelhart, D. & J. McClelland 1986. On learning past tenses of English verbs. In Parallel distributed processing, vol. 2: psychological and biological models, D. Rumelhart & J. McClelland (eds), 216-271. Cambridge, Mass.: MIT Press.
101. Rumelhart, D. & P. Todd 1993. Learning and connectionist representations. Attention and Performance XIV, 3-30.
102. Sadler, D. & E. Shoben 1993. Context effects on semantic domains as seen inanalogy solution. Journal of Experimental Psychology: Learning, Memory, and Cognition 19, 128-47.
103. Schank, R. & R. Abelson 1977. Scripts, plans, goals, and understanding. Hillsdale, New Jersey: Erlbaum.
104. Seidenberg, M. & J. McClelland 1989. A distributed, developmental model ofword recognition and naming. Psychological Review 96, 523-68.
105. Sejnowski, T. 1986. Open questions about computation in the cerebral cortex. In Parallel distributed processing, vol. 2: psychological and biological models, D. Rumelhart & J. McClelland (eds). Cambridge, Mass.: MIT Press.
106. Shanks, D. 1991. Categorization by a connectionist network. Journal ofExperimental Psychology: Learning, Memory, and Cognition 17, 433-43.
107. Shastri, L. & V. Ajjanagadde 1992. From simple associations to systematicreasoning: a connectionist representation of rules, variables and dynamicbindings using temporal synchrony. Behavioural and Brain Sciences 12, 456-78.
108. Shepard, R. 1980. Multidimensional scaling, tree-fitting, and clustering. Science 210, 390-99.
109. Shepard, R. 1987. Toward a universal law of generalization for psychologicalscience. Science 237, 1317-23.
110. Slade, S. 1991. Case-based reasoning: a research paradigm. AI Magazine 13, 42-55.
111. Smith, E. & D. Medin 1981. Categories and concepts. Cambridge, Mass.: HarvardUniversity Press.
112. Smith, E. & S. Sloman 1994. Similarity-versus rule-based categorization. Memory and Cognition 22, 377-86.
113. Smolensky, P. 1988. On the proper treatment of connectionism. Behavioral andBrain Sciences 11, 1-74.
114. Smolensky, P. 1990. Tensor product variable binding and the representation ofsymbolic structures in connectionist systems. Artificial Intelligence 46, 159-215.
115. Solomonoff, R. 1964. A formal theory of inductive inference, part 1. Informationand Control 7, 1-22.
116. Tanaka, J. & M. Taylor 1991. Object categories and expertise: is the basic levelin the eye of the beholder? Cognitive Psychology 23, 457-82.
117. Trabasso, T. & G. Bower 1968. Attention in learning: theory and research. NewYork: John Wiley.
118. Tresp, V., J. Hollatz, S. Ahmad 1993. Network structuring and training usingrule-based knowledge. In Advances in Neural Information Processing 5, C. Giles, S. Hanson, J. Cowan (eds). San Mateo, California: Morgan Kaufman.
119. Tversky, A. 1977. Features of similarity. Psychological Review 84, 327-52.
120. Tversky, A. & I. Gati 1978. Studies of similarity. In Cognition and categorization, E. Rosch & B. Lloyd (eds), 79-98. Hillsdale, New Jersey: Erlbaum.
121. Tversky, A. & I. Gati 1982. Similarity, separability and the triangle inequality. Psychological Review 89, 123-54.
122. Tversky, A. & J. Hutchinson 1986. Nearest neighbour analysis of psychologicalspaces. Psychological Review 93, 3-22.
123. Wallace, C. & D. Boulton 1968. An information measure for classification. Computing Journal 11, 185-95.
124. Wattenmaker, W, G. Dewey, T. Murphy, D. Medin 1986. Linear separability andconcept learning. Cognitive Psychology 18, 158-94.
125. Wattenmaker, W, G. Nakamura, D. Medin 1988. Relationships betweensimilarity-based and explanation-based categorization. In Contemporaryscience and natural explanation, D. Hilton (ed.). Brighton: Harvester.
126. Whittlesea, B. 1987. Preservation of specific experiences in the representationof general knowledge. Journal of Experimental Psychology: Learning, Memory, and Cognition 13, 3-17.
127. Wisniewski, E. & D. Medin 1994. On the interaction of theory and data in conceptlearning. Cognitive Science 18, 221-81.