Learning in a Changing Environment

Journal of Experimental Psychology: General

Volumn 139, Issue 2, 2010, Pages 266-298

  Speekenbrink, Maarten ^a   Shanks, David R ^a  

^a UNIVERSITY COLLEGE LONDON   (United Kingdom)

Author keywords

Dynamic environment; Global versus local learning; Lens model; Multiple cue learning

Indexed keywords

ADULT; ANALYSIS OF VARIANCE; ARTICLE; ASSOCIATION; ATTENTION; COGNITION; ENVIRONMENT; FEMALE; HUMAN; LEARNING; MALE; PROBLEM SOLVING; PSYCHOLOGICAL MODEL;

ADULT; ANALYSIS OF VARIANCE; ATTENTION; COGNITION; CUES; ENVIRONMENT; FEMALE; HUMANS; MALE; MODELS, PSYCHOLOGICAL; PROBABILITY LEARNING; PROBLEM SOLVING;

EID: 77954791770     PISSN: 00963445     EISSN: None     Source Type: Journal    
DOI: 10.1037/a0018620     Document Type: Article

References (80)

1. Anderson N.H. Foundations of information integration theory 1981, Academic Press, New York, NY.
2. Baddeley R.J., Ingram H.A., Miall R.C. System identification applied to a visuomotor task: Near-optimal human performance in a noisy changing task. Journal of Neuroscience 2003, 23:3066-3075.
3. Behrens T.E.J., Woolrich M.W., Walton M.E., Rushworth M.F.S. Learning the value of information in an uncertain world. Nature Neuroscience 2007, 10:1214-1221.
4. Berry D.C., Broadbent D.E. On the relationship between task performance and associated verbalizable knowledge. Quarterly Journal of Experimental Psychology 1984, 36:209-231.
5. Birnbaum M.H. Intuitive numerical prediction. American Journal of Psychology 1976, 89:417-429.
6. Bouton M.E. Context and behavioral processes in extinction. Learning and Memory 2004, 11:485-494.
7. Brehmer B. Single-cue probability learning as a function of the sign and magnitude of the correlation between cue and criterion. Organizational Behavior and Human Performance 1973, 9:377-395.
8. Brehmer B. The psychology of linear judgment models. Acta Psychologica 1994, 87:137-154.
9. Brunswik E. Representative design and probabilistic theory in a functional psychology. Psychological Review 1955, 62:193-217.
10. Busemeyer J.R., Byun E., DeLosh E.L., McDaniel M.A. Learning functional relations based on experience with input-output pairs by humans and artificial neural networks. Knowledge, concepts and categories 1997, 405-437. Psychology Press, Hove, England. K. Lamberts, D. Shanks (Eds.).
11. Busemeyer J.R., Myung I.J., McDaniel M.A. Cue competition effects: Empirical tests of adaptive network learning models. Psychological Science 1993, 4:190-195.
12. Busemeyer J.R., Myung I.J., McDaniel M.A. Cue competition effects: Theoretical implications for adaptive network learning models. Psychological Science 1993, 4:196-202.
13. Cheng S., Sabes P.N. Calibration of visually guided reaching is driven by error-corrective learning and internal dynamics. Journal of Neurophysiology 2007, 97:3057-3069.
14. Chhabra M., Jacobs R.A. Near-optimal human adaptive control across different noise environments. Journal of Neuroscience 2006, 26:10883-10887.
15. Cooksey R.W. The methodology of social judgement theory. Thinking and Reasoning 1996, 2:141-173.
16. Dayan P., Kakade S., Montague P.R. Learning and selective attention. Nature Neuroscience 2000, 3:1218-1223.
17. Dayan P., Long T. Statistical models of conditioning. Advances in neural information processing systems 10: Proceedings of the 1997 conference 1998, MIT Press, Cambridge, MA. M.I. Jordan, M.J. Kearns, S.A. Solla (Eds.).
18. DeLosh E.L., Busemeyer J.R., McDaniel M.A. Extrapolation: The sine qua non for abstraction in function learning. Journal of Experimental Psychology: Learning, Memory, and Cognition 1997, 23:968-986.
19. Dempster A.P., Laird N.M., Rubin D.B. Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society, Series B 1977, 39:1-38.
20. DeShon R.P., Alexander R.A. Goal setting effects on implicit and explicit learning of complex tasks. Organizational Behavior and Human Decision Processes 1996, 65:18-36.
21. Doucet A., de Freitas N., Gordon N. Sequential Monte Carlo methods in practice 2001, Springer, New York, NY.
22. Dudycha A.L., Dumoff M.G., Dudycha L.W. Choice behavior in dynamic environments. Organizational Behavior and Human Performance 1973, 9:328-338.
23. Durbin J., Koopman S.J. Time series analysis by state space methods 2001, Oxford University Press, Oxford, England.
24. Elliott S.W., Anderson J.R. Effect of memory decay on predictions from changing categories. Journal of Experimental Psychology: Learning, Memory, and Cognition 1995, 21:815-836.
25. Evans J.St.B.T., Clibbens J., Cattani A., Harris A., Dennis I. Explicit and implicit processes in multicue judgment. Memory & Cognition 2003, 31:608-618.
26. Ghahramani Z., Hinton G.E. Variational learning for switching state-space models. Neural Computation 2000, 12:831-864.
27. Gilks W.R., Richardson S., Spiegelhalter D.J. Markov chain Monte Carlo in practice 1996, Chapman and Hall, Boca Raton, FL.
28. Gluck M.A., Bower G.H. From conditioning to category learning: An adaptive network model. Journal of Experimental Psychology: General 1988, 117:227-247.
29. Gluck M.A., Shohamy D., Myers C. How do people solve the " weather prediction task" ? Individual variability in strategies for probabilistic category learning. Learning & Memory 2002, 9:408-418.
30. Grant D.A., Berg E. A behavioral analysis of degree of reinforcement and ease of shifting to new responses in a Weigl-type card-sorting problem. Journal of Experimental Psychology 1948, 38:404-411.
31. Griffiths T.L., Tenenbaum J.B. Structure and strength in causal induction. Cognitive Psychology 2005, 51:354-384.
32. Hammond K.R., Wilkins M.M., Todd F.J. A research paradigm for the study of interpersonal learning. Psychological Bulletin 1966, 65:221-232.
33. Harries C., Evans J.St.B.T., Dennis I. Measuring doctors' self-insight into their treatment decisions. Applied Cognitive Psychology 2000, 14:455-477.
34. Harvey A.C. Forecasting, structural time series models and the Kalman filter 1989, Cambridge University Press, Cambridge, England.
35. Juslin P., Karlsson L., Olsson H. Information integration in multiple cue judgment: A division of labor hypothesis. Cognition 2008, 106:259-298.
36. Juslin P., Olsson H., Olsson A.-C. Exemplar effects in categorization and multiple-cue judgment. Journal of Experimental Psychology: General 2003, 132:133-156.
37. Kakade S., Dayan P. Acquisition and extinction in autoshaping. Psychological Review 2002, 109:533-544.
38. Kalish M.L., Lewandowsky S., Kruschke J.K. Population of linear experts: Knowledge partitioning and function learning. Psychological Review 2004, 111:1072-1099.
39. Kalman R.E. A new approach to linear filtering and prediction problems. Transactions of the American Society of Mechanical Engineers, Series D, Journal of Basic Engineering 1960, 82:35-45.
40. Kalman R.E., Bucy R.S. New results in linear filtering and prediction theory. Transactions of the American Society of Mechanical Engineers, Series D, Journal of Basic Engineering 1961, 83:95-108.
41. Kelley H., Busemeyer J. A comparison of models for learning how to dynamically integrate multiple cues in order to forecast continuous criteria. Journal of Mathematical Psychology 2008, 52:218-240.
42. Kelley H., Friedman D. Learning to forecast price. Economic Inquiry 2002, 40:556-573.
43. Knowlton B.J., Mangels J.A., Squire L.R. A neostriatal habit learning system in humans. Science 1996, September 6, 273:1399-1402.
44. Körding K.P., Wolpert D.M. Bayesian integration in sensorimotor learning. Nature 2004, January 15, 427:244-247.
45. Kruschke J.K. ALCOVE: An exemplar-based connectionist model of category learning. Psychological Review 1992, 99:22-44.
46. Lagnado D.A., Newell B.R., Kahan S., Shanks D.R. Insight and strategy in multiple cue learning. Journal of Experimental Psychology: General 2006, 135:162-183.
47. Lindberg L.-A., Brehmer B. Transfer in single-cue probability learning. Organizational Behavior and Human Performance 1976, 16:177-192.
48. Lovibond P.F., Shanks D.R. The role of awareness in Pavlovian conditioning: Empirical evidence and theoretical implications. Journal of Experimental Psychology: Animal Behavior Processes 2002, 28:3-26.
49. Mather G. Foundations of perception 2006, Psychology Press, Hove, England.
50. McDaniel M.A., Busemeyer J.R. The conceptual basis of function learning and extrapolation: Comparison of rule-based and associative-based models. Psychonomic Bulletin & Review 2005, 12:24-42.
51. Medin D., Schaffer M. Context theory of classification learning. Psychological Review 1978, 85:207-238.
52. Milner B. Effects of brain lesions on card sorting. Archives of Neurology 1963, 9:90-100.
53. Murphy K.P. Switching Kalman filters (Tech. Rep. No. 98-10) 1998, Compaq Cambridge Research Lab, Cambridge, England.
54. Naylor J.C., Clark R.D. Intuitive inference strategies in interval learning as a function of magnitude and sign. Organizational Behavior and Human Performance 1968, 3:378-399.
55. Newell B.R., Lagnado D.A., Shanks D.R. Challenging the role of implicit processes in probabilistic category learning. Psychonomic Bulletin & Review 2007, 14:505-511.
56. Nisbett R.E., Wilson T.D. Telling more than we can know: Verbal reports on mental processes. Psychological Review 1977, 84:231-259.
57. Nosofsky R.M. Attention, similarity, and the identification-categorization relationship. Journal of Experimental Psychology: General 1986, 115:39-61.
58. Nosofsky R.M., Kruschke J.K., McKinley S.C. Combining exemplar-based category representations and connectionist learning rules. Journal of Experimental Psychology: Learning, Memory, and Cognition 1992, 18:211-233.
59. Oaksford M., Chater N. Bayesian rationality 2007, Oxford University Press, Oxford, England.
60. Peterson C.R., Hammond K.R., Summers D.A. Multiple probability-learning with shifting weights of cues. American Journal of Psychology 1965, 4:660-663.
61. R: A language and environment for statistical computing [Computer software manual] 2006, R Development Core Team, Available from http://www.R-project.org.
62. Redish A.D., Jensen S., Johnson A., Kurth-Nelson Z. Reconciling reinforcement learning models with behavioral extinction and renewal: Implications for addiction, relapse, and problem gambling. Psychological Review 2007, 114:784-805.
63. Rescorla R.A. Partial reinforcement reduces the associative change produced by nonreinforcement. Journal of Experimental Psychology: Animal Behavior Processes 1999, 25:403-414.
64. Ruffner J.W., Muchinsky P.M. The influence of shifting cue validity distributions and group discussion feedback on multiple cue probability learning. Organizational Behavior and Human Performance 1978, 21:189-208.
65. Schwarz G. Estimating the dimension of a model. Annals of Statistics 1978, 6:461-464.
66. Seger C.A. Implicit learning. Psychological Bulletin 1994, 115:163-196.
67. Shumway R.H., Stoffer S. An approach to time series smoothing and forecasting using the EM algorithm. Journal of Time Series Analysis 1982, 3:253-264.
68. Silverman B.W. Density estimation for statistics and data analysis 1986, Chapman and Hall, London, England.
69. Slovic P., Lichtensteln S. Comparison of Bayesian and regression approaches to the study of information processing in judgment. Organizational Behavior and Human Performance 1971, 6:649-744.
70. Speekenbrink M., Channon S., Shanks D.R. Learning strategies in amnesia. Neuroscience and Biobehavioral Reviews 2008, 32:292-310.
71. Speekenbrink M., Shanks D.R. Through the looking glass: A dynamic lens model approach to learning in MCPL tasks. The probabilistic mind: Prospects for rational models of cognition 2008, 409-429. Oxford University Press, Oxford, England. N. Chater, M. Oaksford (Eds.).
72. Summers D.A. Adaptation to change in multiple probability tasks. American Journal of Psychology 1969, 8:235-240.
73. Sutton R.S. Gain adaptation beats least squares?. Proceedings of the 7th Yale Workshop on Adaptive and Learning Systems 1992, 161-166. Yale University Press, New Haven, CT. K.S. Narendra (Ed.).
74. Tenenbaum J.B., Griffiths T.L., Kemp C. Theory-based Bayesian models of inductive learning and reasoning. Trends in Cognitive Sciences 2006, 10:309-318.
75. West M., Harrison J. Bayesian forecasting and dynamic models 1997, Springer, New York, NY. 2nd ed.
76. Wigton R.S. Social judgment theory and medical judgment. Thinking and Reasoning 1996, 2:175-190.
77. Wolpert D.M., Ghahramani Z., Jordan M.I. An internal model for sensorimotor integration. Science 1995, September 29, 269:1880-1882.
78. Wu L.S.-Y., Pai J.S., Hosking J.R.M. An algorithm for estimating parameters of state-space models. Statistics and Probability Letters 1996, 28:99-106.
79. York K.M., Doherty M.E., Kamouri J. The influence of cue unreliability on judgment in a multiple cue probability learning task. Organizational Behavior and Human Performance 1987, 39:303-317.
80. Yu A.J., Dayan P. Uncertainty, neuromodulation, and attention. Neuron 2005, 46:681-692.