On the interaction between exemplar-based concepts and a response scaling process

Journal of Mathematical Psychology

Volumn 51, Issue 2, 2007, Pages 85-98

  Navarro, Daniel J ^a  

^a UNIVERSITY OF ADELAIDE   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 33847655699     PISSN: 00222496     EISSN: 10960880     Source Type: Journal    
DOI: 10.1016/j.jmp.2006.11.003     Document Type: Article

References (47)

1. Ashby F.G., and Maddox W.T. Relations between prototype, exemplar, and decision bound models of categorization. Journal of Mathematical Psychology 37 (1993) 372-400
2. Bruner J.S., Goodnow J.J., and Austin G.A. A study of thinking (1956), Wiley, New York
3. Cox T.F., and Cox M.A.A. Multidimensional scaling (1994), Chapman & Hall, London
4. Feller W. An introduction to probability theory and its applications. 3rd ed. (1968), Wiley, New York
5. Gigerenzer G., and Todd P.M. Simple heuristics that make us smart (1999), Oxford University Press, New York
6. Hosmer D.W., and Lemeshow S. Applied logistic regression (2000), Wiley, New York
7. Jaynes E.T. Probability theory: The logic of science (2003), Cambridge University Press, Cambridge, UK
8. Kalman R.E. A new approach to linear filtering and prediction problems. Transactions of the ASME-Journal of Basic Engineering, Series D 82 (1960) 35-45
9. Komatsu L.K. Recent views of conceptual structure. Psychological Bulletin 112 (1992) 500-526
10. Kontkanen P., Myllymäki P., Buntine W., Rissanen J., and Tirri H. An MDL framework for data clustering. In: Grünwald P., Myung I.J., and Pitt M.A. (Eds). Advances in minimum description length: Theory and applications (2005), MIT Press, Cambridge, MA 323-354
11. Kruschke J.K. ALCOVE: An exemplar-based connectionist model of category learning. Psychological Review 99 (1992) 22-44
12. Lee M.D., and Webb M.R. Modeling individual differences in cognition. Psychonomic Bulletin & Review 12 (2005) 605-621
13. Love B.C., Medin D.L., and Gureckis T.M. SUSTAIN: A network model of category learning. Psychological Review 111 (2004) 309-332
14. Luce, R. D. (1963). Detection and recognition. In R. D. Luce, R. R. Bush, & E. Galanter (Eds.) Handbook of mathematical psychology (Vol. 1) (pp. 103-190). New York: Wiley.
15. Luce R.D. Response times: Their role in inferring elementary mental organization (1986), Oxford University Press, New York, NY
16. Manski C.F. The structure of random utility models. Theory and Decision 8 (1977) 229-254
17. McFadden D. Conditional logit analysis of qualitative choice behavior. In: Zarembka P. (Ed). Frontiers in econometrics (1974), Academic Press, New York 105-142
18. Medin D.L., and Schaffer M.M. Context theory of classification learning. Psychological Review 85 (1978) 207-238
19. Medin D.L., and Schwanenflugel P.J. Linear separability in classification learning. Journal of Experimental Psychology: Human Learning and Memory 7 (1981) 241-253
20. Minkowski H. On positive quadratic forms and on algorithms suggesting continued fractions. Journal für die reine und angewandte Mathematik 107 (1891) 278-297
21. Murphy G.L. The big book of concepts (2002), MIT Press, Cambridge, MA
22. Navarro D.J. From natural kinds to complex categories. In: Sun R., and Miyake N. (Eds). Proceedings of the 27th annual conference of the cognitive science society (2006), Lawrence Erlbaum, Mahwah, NJ 621-626
23. Navarro D.J., Griffiths T.L., Steyvers M., and Lee M.D. Modeling individual differences using Dirichlet processes. Journal of Mathematical Psychology 50 (2006) 101-122
24. Navarro, D. J., & Lee, M. D. (2005). An application of minimum description length clustering to partitioning learning curves. The 2005 IEEE International Symposium on Information Theory (pp. 587-591). Piscataway, NJ:IEEE.
25. Nosofsky R.M. Choice, similarity, and the context theory of classification. Journal of Experimental Psychology: Learning, Memory and Cognition 10 (1984) 104-114
26. Nosofsky R.M. Attention, similarity and the identification-categorization relationship. Journal of Experimental Psychology: General 115 (1986) 39-57
27. Nosofsky R.M. Optimal performance and exemplar models of classification. In: Oaksford M., and Chater N. (Eds). Rational models of cognition (1998), Oxford University Press, New York 218-247
28. Nosofsky R.M., and Alfonso-Reese L.A. Effects of similarity and practice on speeded classification response times and accuracies: Further tests of an exemplar-retrieval model. Memory & Cognition 27 (1999) 78-93
29. Nosofsky R.M., and Palmeri T.J. An exemplar-based random walk model of speeded classification. Psychological Review 104 (1997) 266-300
30. Nosofsky R.M., and Zaki S.R. Exemplar and prototype models revisited: Response strategies, selective attention, and stimulus generalization. Journal of Experimental Psychology: Learning, Memory, and Cognition 28 (2002) 924-940
31. Osherson D.N., Smith E.E., Wilkie O., Lopez A., and Shafir E. Category-based induction. Psychological Review 97 (1990) 185-200
32. Pitt M.A., Myung I.J., and Zhang S. Toward a method of selecting among computational models of cognition. Psychological Review 109 (2002) 472-491
33. Ratcliff R. A theory of memory retrieval. Psychological Review 85 (1978) 59-108
34. Reed S.K. Pattern recognition and categorization. Cognitive Psychology 3 (1972) 382-407
35. Rosch E. Principles of categorization. In: Rosch E., and Lloyd B.B. (Eds). Cognition and categorization (1978), Erlbaum, Hillsdale, NJ 27-77
36. Rosch E., and Mervis C.B. Family resemblances: Studies in the internal structure of categories. Cognitive Psychology 7 (1975) 573-605
37. Schervish M.J. Theory of statistics (1995), Springer, New York
38. Shepard R.N. Stimulus and response generalization: A stochastic model relating generalization to distance in psychological space. Psychometrika 22 (1957) 325-345
39. Shepard R.N. Toward a universal law of generalization for psychological science. Science 237 (1987) 1317-1323
40. Smith J.D., and Minda J.P. Prototypes in the mist: The early epochs of category learning. Journal of Experimental Psychology: Learning, Memory and Cognition 24 (1998) 1411-1436
41. Smith J.D., and Minda J.P. Distinguishing prototype-based and exemplar-based processes in dot-pattern category learning. Journal of Experimental Psychology: Learning, Memory and Cognition 28 (2002) 800-811
42. Stone M. Models for choice-reaction time. Psychometrika 25 (1960) 251-260
43. Tenenbaum, J. B., & Griffiths, T. L. (2001). Generalization, similarity, and Bayesian inference Behavioral and Brain Sciences, 24, 629-641 & 762-778.
44. Vickers D. Decision processes in visual perception (1979), Academic Press, New York
45. Wald A. Sequential analysis (1947), Wiley, New York
46. Wald A., and Wolfowitz J. Optimum character of the sequential probability ratio test. Annals of Mathematical Statistics 19 (1948) 326-339
47. Wittgenstein L. Philosophical investigations (1953), Blackwell, Oxford, UK