Computational Models of Decision Making

Blackwell Handbook of Judgment and Decision Making

Volumn , Issue , 2008, Pages 133-154

  Busemeyer, Jerome R ^a   Johnson, Joseph G ^a  

^a INDIANA UNIVERSITY   (United States)

Author keywords

Computational models; Decision; Decision theory; Intuitive discussion; Lateral inhibition

Indexed keywords

EID: 84889395726     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1002/9780470752937.ch7     Document Type: Chapter

References (73)

1. Anderson, J. A. (1997) An Introduction to Neural Networks. Cambridge, MA: MIT Press.
2. Aschenbrenner, K. M., Albert, D., & Schmalhofer, F. (1984) Stochastic choice heuristics, Acta Psychologica, 56(1-3), 153-66.
3. Ashby, F. G. (2000) A stochastic version of general recognition theory, Journal of Mathematical Psychology, 44, 310-29.
4. Birnbaum, M. H. & Sutton, S. E. (1992) Scale convergence and utility measurement, Organizational Behavior and Human Decision Processes, 52, 183-215.
5. Birnbaum, M. H., Yeary, S., Luce, R. D., & Zhou, L. (2002, submitted) Contingent valuation, endowment, or viewpoint effects: Testing properties in judgments of buying and selling prices of lotteries.
6. Busemeyer, J. R. (1985) Decision making under uncertainty: Simple scalability, fixed sample, and sequential sampling models, Journal of Experimental Psychology: Learning, Memory, and Cognition, 11, 538-64.
7. Busemeyer, J. R. & Diederich, A. (2002) Survey of decision field theory, Mathematical Social Sciences, 43, 345-70.
8. Busemeyer, J. R. & Goldstein, W. M. (1992) Linking together different measures of preference: A dynamic model of matching derived from decision field theory, Organizational Behavior and Human Decision Processes, 52, 370-96.
9. Busemeyer, J. R. & Townsend, J. T. (1992) Fundamental derivations from decision field theory, Mathematical Social Sciences, 23, 255-82.
10. Busemeyer, J. R. & Townsend, J. T. (1993) Decision field theory: A dynamic cognition approach to decision making, Psychological Review, 100, 432-59.
11. Busemeyer, J. R., Townsend, J. T., & Stout, J. C. (2002) Motivational underpinnings of utility in decision making: Decision field theory analysis of deprivation and satiation. In S. Moore (ed.), Emotional Cognition. Amsterdam: John Benjamins.
12. DeGroot, M. H. (1970) Optimal Statistical Decisions. New York: McGraw-Hill.
13. Dhar, R., Nowlis, S. M., & Sherman, S. J. (2000) Trying hard or hardly trying: An analysis of context effects in choice, Journal of Consumer Psychology, 9, 189-200.
14. Diederich, A. (1997) Dynamic stochastic models for decision making under time constraints, Journal of Mathematical Psychology, 41(3), 260-74.
15. Diederich, A. (2003a) Decision making under conflict: Decision time as a measure of conflict strength, Psychonomic Bulletin and Review, 10(1), 167-75.
16. Diederich, A. (2003b) MDFT account of decision making under time pressure, Psychonomic Bulletin and Review, 10(1), 157-66.
17. Diederich, A. & Busemeyer, J. R. (1999) Conflict and the stochastic dominance principle of decision making, Psychological Science, 10, 353-9.
18. Diederich, A. & Busemeyer, J. R. (2003) Simple matrix methods for analyzing diffusion models of choice probability, choice response time, and simple response time, Journal of Mathematical Psychology, 47(3), 304-22.
19. Dougherty, M. R. P., Gettys, C. F., & Ogden, E. E. (1999) MINERVA-DM: A memory process model for judgements of likelihood, Psychological Review, 106, 108-209.
20. Dror, I. E., Busemeyer, J. R., & Basola, B. (1999) Decision making under time pressure: An independent test of sequential sampling models, Memory and Cognition, 27, 713-25.
21. Fischer, G. W., Jia, J., & Luce, M. F. (2000) Attribute conflict and preference uncertainty: The RandMAU model, Management Science, 46, 669-84.
22. Glockner, A. (2002) The maximizing consistency heuristic: Parallel processing in human decision making, thesis, Heidelberg University.
23. Gold, J. I. & Shadlen, M. N. (2001) Neural computations that underlie decisions about sensory stimuli, Trends in Cognitive Neuroscience, 5, 10-16.
24. Gold, J. I. & Shadlen, M. N. (2002) Banburismas and the brain: Decoding the relationship between sensory stimuli, decisions, and reward, Neuron, 36, 299-308.
25. Goldstein, W. & Einhorn, H. J. (1987) Expression theory and the preference reversal phenomena, Psychological Review, 94, 236-54.
26. Gonzàlez-Vallejo, C. (2002) Making trade-offs: A probabilistic and context-sensitive model of choice behavior, Psychological Review, 109(1), 137-55.
27. Gratton, G., Coles, M. G., Sirevaag, E. J., Erickson, C. J., & Donchin, E. (1988) Pre-and poststimulus activation of response channels: A psychophysiological analysis, Journal of Experimental Psychology: Human Perception and Performance, 14, 331-44.
28. Grossberg, S. (1988) Neural Networks and Natural Intelligence. Cambridge, MA: MIT Press.
29. Grossberg, S. & Gutowski, W. E. (1987) Neural dynamics of decision making under risk: Affective balance and cognitive-emotional interactions, Psychological Review, 94(3), 300-18.
30. Guo, F. Y. & Holyoak, K. J. (2002) Understanding similarity in choice behavior: A connectionist model. In W. D. Gray and C. D. Schunn (eds.), Proceedings of the Twenty-fourth Annual Conference of the Cognitive Science Society (pp. 393-8). Mahwah, NJ: Erlbaum.
31. Heath, T. B. & Chatterjee, S. (1995) Asymmetric decoy effects on lower-quality versus higherquality brands: Meta analytic and experimental evidence, Journal of Consumer Research, 22, 268-84.
32. Hershey, J. C. & Schoemaker, P. J. H. (1985) Probability versus certainty equivalence methods in utility measurement: Are they equivalent? Mangement Science, 31, 1213-31.
33. Holyoak, K. J. & Simon, D. (1999) Bidirectional reasoning in decision making by constraint satisfaction, Journal of Experimental Psychology: General, 128(1), 3-31.
34. Huber, J., Payne, J. W., & Puto, C. (1982) Adding asymmetrically dominated alternatives: Violations of regularity and the similarity hypothesis, Journal of Consumer Research, 9(1), 90-8.
35. Johnson, J. G. & Busemeyer, J. R. (in press) Rule-based decision field theory: A dynamic computational model of transitions among decision-making strategies. To appear in T. Betsch (ed.), The Routines of Decision Making. Mahwah, NJ: Erlbaum.
36. Kahneman, D., Knetsch, J., & Thaler, R. (1990) Experimental tests of the endowment effect and the Coase theorem, Journal of Political Economy, 98(6), 1325-48.
37. Laming, D. R. (1968) Information Theory of Choice-reaction Times. New York: Academic Press.
38. Levin, S. J. & Levine, D. S. (1996) Multiattribute decision making in context: A dynamic neural network methodology, Cognitive Science, 20, 271-99.
39. Lichtenstein, S. & Slovic, P. (1971) Reversals of preference between bids and choices in gambling decisions, Journal of Experimental Psychology, 89, 46-55.
40. Link, S. W. & Heath, R. (1975) A sequential theory of psychological discrimination, Psychometrika, 40, 77-111.
41. Luce, R. D. (1959) Individual Choice Behavior: A Theoretical Analysis. New York: Wiley.
42. Luce, R. D. (2000) Utility of Gains and Losses. Mahwah, NJ: Erlbaum.
43. Luce, R. D. & Suppes, P. (1965) Preference, utility, and subjective probability. In R. D. Luce, R. R. Bush, and E. Galanter (eds.), Handbook of Mathematical Psychology (vol. 3, pp. 249-410). New York: Wiley.
44. Marr, D. (1982) Vision. Cambridge, MA: MIT Press.
45. Mellers, B. A. & Biagini, K. (1994) Similarity and choice, Psychological Review, 101, 505-18.
46. Montgomery, H. (1989) From cognition to action: The search for dominance in decision making. In H. Montgomery and O. Svenson (eds.), Process and Structure in Human Decision Making (pp. 23-49). New York: Wiley.
47. Nosofsky, R. M. & Palmeri, T. J. (1997) An exemplar based random walk model of speeded classification, Psychological Review, 104, 266-300.
48. Payne, J. W., Bettman, J. R., & Johnson, E. J. (1993) The Adaptive Decision Maker. New York: Cambridge University Press.
49. Platt, M. L. (2002) Neural correlates of decisions, Current Opinion in Neurobiology, 12(2), 141-8.
50. Plott, C. R. (1996) Rational individual behavior in markets and social processes: The discovered preference hypothesis. In K. Arrow, E. Collombatto, M. Perlaman, and C. Schmidt (eds.), The Rational Foundations of Economic Behavior. London: Macmillan.
51. Ratcliff, R. (1978) A theory of memory retrieval, Psychological Review, 85, 59-108.
52. Read, S. J., Vanman, E. J., & Miller, L. C. (1997) Connectionism, parallel constraint satisfaction and gestalt principles: (Re)introducting cognitive dynamics to social psychology, Personality and Social Psychology Review, 1, 26-53.
53. Roe, R., Busemeyer, J. R., & Townsend, J. T. (2001) Multi-alternative decision field theory: A dynamic connectionist model of decision-making, Psychological Review, 108, 370-92.
54. Rumelhart, D., & McClelland, J. L. (1986) Parallel Distributed Processing: Explorations in the Microstructure of Cognition (vol. 1). Cambridge, MA: MIT Press.
55. Samuelson, W. & Zeckhauser, R. (1988) Status quo bias in decision making, Journal of Risk and Uncertainty, 1, 7-59.
56. Schall, J. D. (2001) Neural basis of deciding, choosing, and acting, Nature Reviews: Neuroscience, 2, 33-42.
57. Simonson, I. (1989) Choice based on reasons: The case of attraction and compromise effects, Journal of Consumer Research, 16, 158-74.
58. Slovic, P. & S. Lichtenstein. (1983) Preference reversals: A broader perspective, American Economic Review, 73, 596-605.
59. Smith, P. L. (1995) Psychophysically principled models of visual simple reaction time, Psychological Review, 102(3), 567-93.
60. Svenson, O. (1992) Differentiation and consolidation theory of human decision making: A frame of reference for the study of pre-and post-decision processes, Acta Psychologica, 80, 143-68.
61. Svenson, O. & Edland, A. (1987) Change of preferences under time pressure: Choices and judgments, Scandinavian Journal of Psychology, 28, 322-30.
62. Thagard, P. & Millgram, E. (1995) Inference to the best plan: A coherence theory of decision. In A. Ram and D. B. Leake (eds.), Goal-driven Learning (pp. 439-54). Cambridge, MA: MIT Press.
63. Thurstone, L. L. (1959) The Measurement of Values. Chicago: University of Chicago Press.
64. Townsend, J. T. & Busemeyer, J. R. (1995) Dynamic representation of decision-making. In R. F. Port and T. van Gelder (eds.), Mind as Motion (pp. 101-20). Cambridge, MA: MIT Press.
65. Tversky, A. (1969) Intransitivity of preferences, Psychological Review, 76, 31-48.
66. Tversky, A. (1972) Elimination by aspects: A theory of choice, Psychological Review, 79(4), 281-99.
67. Tversky, A. & Kahneman, D. (1991) Loss aversion in riskless choice: A reference dependent model, Quarterly Journal of Economics, 106, 1039-61.
68. Tversky, A., Sattath, S., & Slovic, P. (1988) Contingent weighting in judgment and choice, Psychological Review, 95, 371-384.
69. Tversky, A. & Simonson, I. (1993) Context dependent preferences, Management Science, 39, 1179-89.
70. Usher, M. & McClelland, J. L. (2001) On the time course of perceptual choice: A model based on principles of neural computation, Psychological Review, 108, 550-92.
71. Usher, M. & McClelland, J. L. (2002) Decisions, decisions: Loss aversion, information leakage, and inhibition in multi-attribute choice situations. Unpublished note.
72. Vickers, D. (1979) Decision Processes in Visual Perception. New York: Academic Press.
73. Wallsten, T. S. & Barton, C. (1982) Processing probabilistic multidimensional information for decisions, Journal of Experimental Psychology: Learning, Memory, and Cognition, 8, 361-84.