Putting the psychology back into psychological models: Mechanistic versus rational approaches

Memory and Cognition

Volumn 36, Issue 6, 2008, Pages 1057-1065

  Sakamoto, Yasuaki ^a   Jones, Matt ^b   Love, Bradley C ^c  

^a STEVENS INSTITUTE OF TECHNOLOGY   (United States)

^b UNIVERSITY OF COLORADO   (United States)

^c UNIVERSITY OF TEXAS AT AUSTIN   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; CONTROLLED STUDY; HUMAN; HUMAN EXPERIMENT; LEARNING; NORMAL HUMAN; OUTCOME ASSESSMENT; PREDICTION; PROBABILITY; PSYCHOLOGY; TRAINING;

BEHAVIOR; CONCEPT FORMATION; DISCRIMINATION LEARNING; FEEDBACK, PSYCHOLOGICAL; GENERALIZATION, STIMULUS; HUMANS; MEMORY, SHORT-TERM; MODELS, PSYCHOLOGICAL; ORIENTATION; PATTERN RECOGNITION, VISUAL; PSYCHOPHYSICS; SIZE PERCEPTION; SOCIAL ENVIRONMENT; TRANSFER (PSYCHOLOGY);

EID: 54949129754     PISSN: 0090502X     EISSN: None     Source Type: Journal    
DOI: 10.3758/MC.36.6.1057     Document Type: Article

References (30)

1. ANDERSON, J. R. (1990). The adaptive character of thought. Hillsdale, NJ: Erlbaum.
2. ANDERSON, J. R. (1991a). The adaptive nature of human categorization. Psychological Review, 98, 409-429.
3. ANDERSON, J. R. (1991b). Is human cognition adaptive? Behavioral & Brain Sciences, 14, 471-484.
4. CHATER, N., & OAKSFORD, M. (1999). Ten years of the rational analysis of cognition. Trends in Cognitive Sciences, 3, 57-65.
5. CHATER, N., TENENBAUM, J. B., & YUILLE, A. (2006). Probabilistic models of cognition: Where next? Trends in Cognitive Sciences, 10, 292-293.
6. CLAPPER, J. P. (2006). When more is less: Negative exposure effects in unsupervised learning. Memory & Cognition, 34, 890-902.
7. COHEN, A. L., NOSOFSKY, R. M., & ZAKI, S. R. (2001). Category variability, exemplar similarity, and perceptual classification. Memory & Cognition, 29, 1165-1175.
8. ELLIOTT, S. W., & ANDERSON, J. R. (1995). Effect of memory decay on predictions from changing categories. Journal of Experimental Psychology: Learning, Memory, & Cognition, 21, 815-836.
9. FELDMAN, J. (2000). Minimization of Boolean complexity in human concept learning. Nature, 407, 630-633.
10. FRIED, L. S., & HOLYOAK, K. J. (1984). Induction of category distributions: A framework for classification learning. Journal of Experimental Psychology: Learning, Memory, & Cognition, 10, 234-257.
11. GREEN, D. M., & SWETS, J. A. (1966). Signal detection theory and psychophysics. New York: Wiley.
12. GRIFFITHS, T. L., KEMP, C., & TENENBAUM, J. B. (2008). Bayesian models of cognition. In R. Sun (Ed.), Cambridge handbook of computational psychology (pp. 59-100). Cambridge: Cambridge University Press.
13. GRIFFITHS, T. L., & TENENBAUM, J. B. (2006). Optimal predictions in everyday cognition. Psychological Science, 17, 767-773.
14. HAHN, U., BAILEY, T. M., & ELVIN, L. B. C. (2005). Effects of category diversity on learning, memory, and generalization. Memory & Cognition, 33, 289-302.
15. KRUSCHKE, J. K. (1992). ALCOVE: An exemplar-based connectionist model of category learning. Psychological Review, 99, 22-44.
16. LOVE, B. C., & JONES, M. (2006). The emergence of multiple learning systems. In R. Sun & N. Miyake (Eds.), Proceedings of the 28th Annual Conference of the Cognitive Science Society (pp. 507-512). Mahwah, NJ: Erlbaum.
17. LOVE, B. C., MEDIN, D. L., & GURECKIS, T. M. (2004). SUSTAIN: A network model of human category learning. Psychological Review, 111, 309-332.
18. MADDOX, W. T., & ASHBY, F. G. (1998). Selective attention and the formation of linear decision boundaries: Comment on McKinley and Nosofsky (1996). Journal of Experimental Psychology: Human Perception & Performance, 24, 301-321.
19. MARR, D. (1982). Vision. San Francisco: Freeman.
20. MEDIN, D. L., & BETTGER, J. G. (1994). Presentation order and recognition of categorically related examples. Psychonomic Bulletin & Review, 1, 250-254.
21. MEDIN, D. L., & SCHAFFER, M. M. (1978). Context theory of classification learning. Psychological Review, 85, 207-238.
22. NOSOFSKY, R. M., PALMERI, T. J., & MCKINLEY, S. C. (1994). Ruleplus-exception model of classification learning. Psychological Review, 101, 53-79.
23. ONO, H. (1967). Difference threshold for stimulus length under simultaneous and nonsimultaneous viewing conditions. Perception & Psychophysics, 2, 201-207.
24. REED, S. K. (1972). Pattern recognition and categorization. Cognitive Psychology, 3, 382-407.
25. RIPS, L. J. (1989). Similarity, typicality, and categorization. In S. Vosniadou & A. Ortony (Eds.), Similarity and analogical reasoning (pp. 21-59). New York: Cambridge University Press.
26. RODRIGUES, P. M., & MURRE, J. M. J. (2007). Rules-plus-exception tasks: A problem for exemplar models? Psychonomic Bulletin & Review, 14, 640-646.
27. SAKAMOTO, Y., MATSUKA, T., & LOVE, B. C. (2004). Dimension-wide vs. exemplar-specific attention in category learning and recognition. In M. Lovett, C. Schunn, C. Lebiere, & P. Munro (Eds.), Proceedings of the 6th International Conference of Cognitive Modeling (pp. 261-266). Mahwah, NJ: Erlbaum.
28. TENENBAUM, J. B., & GRIFFITHS, T. L. (2001). Generalization, similarity and Bayesian inference. Behavioral & Brain Sciences, 24, 629-640.
29. TOWNSEND, J. T. (1974). Issues and models concerning the processing of a finite number of inputs. In B. H. Kantowitz (Ed.), Human information processing: Tutorials in performance and cognition (pp. 133-186). Hillsdale, NJ: Erlbaum.
30. ZAKI, S. R., & HOMA, D. (1999). Concepts and transformational knowledge. Cognitive Psychology, 39, 69-115.