Testing the psychological validity of cluster construction biases

Proceedings of the 36th Annual Meeting of the Cognitive Science Society, CogSci 2014

Volumn , Issue , 2014, Pages 122-127

  Austerweil, Joseph L ^a  

^a BROWN UNIVERSITY   (United States)

Author keywords

Bayesian modeling; Categorization; Clustering; Connectionist modeling

Indexed keywords

BAYESIAN NETWORKS; BEHAVIORAL RESEARCH; MARKOV PROCESSES; MONTE CARLO METHODS;

BAYESIAN MODELLING; CATEGORIZATION; CLUSTER CONSTRUCTION; CLUSTERINGS; COMPUTATIONAL WORK; CONNECTIONIST MODELS; HUMAN BEHAVIORS; HUMAN PERFORMANCE; MARKOV CHAIN MONTE CARLO; MARKOV CHAIN MONTE-CARLO;

STATISTICAL TESTS;

EID: 84938868339     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (25)

1. Aldous, D. (1985). Exchangeability and related topics. In École d'Été de probabilités de Saint-Flour xiii (pp. 1-198). Berlin: Springer.
2. Aldous, D., & Diaconis, P. (1986). Shuffling cards and stopping times. The American Mathematical Monthly, 93(5), 333-348.
3. Anderson, J. R. (1991). The adaptive nature of human categorization. Psychological Review, 98(3), 409-429.
4. Antoniak, C. (1974). Mixtures of Dirichlet processes with applications to Bayesian nonparametric problems. The Annals of Statistics, 2, 1152-1174.
5. Austerweil, J. L., Friesen, A. L., & Griffiths, T. L. (2011). An ideal observer model for identifying the reference frames of objects. In Advances in NIPS 24.
6. Austerweil, J. L., Gershman, S. J., Tenenbaum, J. B., & Griffiths, T. L. (in press). Structure and flexibility in Bayesian models of cognition. In J. R. Busemeyer, J. T. Townsend, Z. J. Wang, & A. Eidels (Eds.), Oxford Handbook of Computational and Mathematical Psychology. Oxford University Press.
7. Blackwell, D., & MacQueen, J. (1973). Ferguson distributions via Polya urn schemes. The Annals of Statistics, 1, 353-355.
8. Claeskens, G., & Hjort, N. L. (2008). Model selection and model averaging. Cambridge: Cambridge Univ. Press.
9. Ferguson, T. (1973). A Bayesian analysis of some nonparametric problems. The Annals of Statistics, 1, 209-230.
10. Gershman, S., Blei, D., & Niv, Y. (2010). Context, learning, and extinction. Psychological Review, 117(1), 197-209.
11. Gilks, W., Richardson, S., & Spiegelhalter, D. J. (1996). Markov chain Monte Carlo in practice. Chapman and Hall.
12. Goldwater, S., Griffiths, T. L., & Johnson, M. (2009). A Bayesian framework for word segmentation: Exploring the effects of context. Cognition, 112, 21-54.
13. Griffiths, T. L., & Kalish, M. L. (2007). Language evolution by iterated learning with Bayesian agents. Cognitive Science, 31(3), 441-480.
14. Kemp, C., Tenenbaum, J., Niyogi, S., & Griffiths, T. (2010). A probabilistic model of theory formation. Cognition, 114(2), 165-196.
15. Love, B. C., Medin, D. L., & Gureckis, T. M. (2004). SUSTAIN: A network model of category learning. Psychological Review, 111, 309-332.
16. Martin, J. B., Griffiths, T. L., & Sanborn, A. N. (2012). Testing the efficiency of Markov chain Monte Carlo with people using facial affect categories. Cognitive Science, 36, 150-162.
17. Medin, D. L., & Schaffer, M. M. (1978). Context theory of classification learning. Psychological Review, 85, 207-238.
18. Neal, R. M. (1998). Markov chain sampling methods for Dirichlet process mixture models (Tech. Rep. No. 9815). Department of Statistics, University of Toronto.
19. Nosofsky, R. M. (1986). Attention, similarity, and the identification-categorization relationship. JEP: General, 115(1), 39-57.
20. Pitman, J. (2002). Combinatorial stochastic processes. (Notes for Saint Flour Summer School)
21. Pothos, E. M., Perlmann, A., Bailey, T. M., Kurtz, K., Edwards, D. J., Hines, P., & McDonnell, J. V. (2011). Measuring category intuitiveness in unconstrained categorization tasks. Cognition, 121, 83-100.
22. Reed, S. K. (1972). Pattern recognition and categorization. Cognitive Psychology, 3, 393-407.
23. Sanborn, A. N., Griffiths, T. L., & Shiffrin, R. (2010). Uncovering mental representations with Markov chain Monte Carlo. Cognitive Psychology, 60, 63-106.
24. Shanks, D. R., Tunney, R. J., & McCarthy, J. D. (2002). A re-examination of probability matching and rational choice. Journal of Behavioral Decision Making, 15, 233-250.
25. Smith, J. D., & Minda, J. P. (1998). Prototypes in the mist: The early epochs of category learning. JEP:LMC, 24(6), 1411-1436.