Hostname: page-component-89b8bd64d-r6c6k Total loading time: 0 Render date: 2026-05-11T13:23:21.687Z Has data issue: false hasContentIssue false
  • English
  • Français

Is human cognition adaptive?

Published online by Cambridge University Press:  19 May 2011

John R. Anderson
John R. Anderson
Affiliation:
Psychology Department, Carnegie Mellon University, Pittsburgh, PA 15213-3890, Electronic mail: anderson@psy.cmu.edu
Get access Rights & Permissions [Opens in a new window]

Abstract

Can the output of human cognition be predicted from the assumption that it is an optimal response to the information-processing demands of the environment? A methodology called rational analysis is described for deriving predictions about cognitive phenomena using optimization assumptions. The predictions flow from the statistical structure of the environment and not the assumed structure of the mind. Bayesian inference is used, assuming that people start with a weak prior model of the world which they integrate with experience to develop stronger models of specific aspects of the world. Cognitive performance maximizes the difference between the expected gain and cost of mental effort. (1) Memory performance can be predicted on the assumption that retrieval seeks a maximal trade-off between the probability of finding the relevant memories and the effort required to do so; in (2) categorization performance there is a similar trade-off between accuracy in predicting object features and the cost of hypothesis formation; in (3) casual inference the trade-off is between accuracy in predicting future events and the cost of hypothesis formation; and in (4) problem solving it is between the probability of achieving goals and the cost of both external and mental problem-solving search. The implemention of these rational prescriptions in neurally plausible architecture is also discussed.

Keywords

Bayescategorizationcausal inferencecomputationmemoryoptimalityproblem solvingrationality

Information

Type
Target Article
Information
Behavioral and Brain Sciences , Volume 14 , Issue 3 , September 1991 , pp. 471 - 485
Copyright
Copyright © Cambridge University Press 1991

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

Alcock, J. (1989) Animal behavior. Sinauer. [DWM]Google Scholar
Anderson, J. R. (1983) The architecture of cognition. Harvard University Press. [aJRA, RLC]Google Scholar
Anderson, J. R. (1978) Arguments concerning representations for mental imagery. Psychological Review 85:249–77. [rJRA]CrossRefGoogle Scholar
Anderson, J. R. (1987) Methodologies for studying human knowledge. Behavioral and Brain Sciences 10:467–505. [rJRA]CrossRefGoogle Scholar
Anderson, J. R. (1990a) The adaptive character of thought. Erlbaum. [arJRA, RLC, DWM, TRS]Google Scholar
Anderson, J. R. (1990b) Cognitive psychology and its implications, 3rd ed. W. H. Freeman. [aJRA]Google Scholar
Anderson, J. R. (in press) The place of cognitive architectures in a rational analysis. In: Architectures for intelligence, ed. vanLehn, K.. Erlbaum. [aJRA]Google Scholar
Anderson, J. R. & Kushmerick, N. (1990) A rational analysis of production system architecture. Paper presented at the 31st Annual Meeting of the Psychonomic Society, November 16–18. [aJRA]Google Scholar
Anderson, J. R. & Matessa, M. (1990) A rational analysis of categorization. In: Proceedings of the Seventh International Machine Learning Conference, Palo Alto, CA, ed. Kaufmann, M.. [aJRA]CrossRefGoogle Scholar
Anderson, J. R. & Matessa, M. (submitted) Explorations of an incremental, Bayesian algorithm for categorization. Machine Learning. [rJRA]Google Scholar
Anderson, J. R. & Milson, R. (1989) Human memory: An adaptive perspective. Psychological Review 96(4):703–19. [aJRA, WS]CrossRefGoogle Scholar
Anderson, N. H. (1981) Information integration theory. Academic Press. [H-GG]Google Scholar
Arkes, H. R. & Harkness, A. R. (1983) Estimates of contingency between two dichotomous variables. Journal of Experimental Psychology: General 112:117–35. [aJRA]CrossRefGoogle Scholar
Atwood, M. E. & Poison, P. G. (1976) A process model for water jug problems. Cognitive Psychology 8:191–216. [aJRA]CrossRefGoogle Scholar
Bahrick, H. P. (1979) Maintenance of knowledge: Questions about memory we forget to ask. Journal of Experimental Psychology: General 108:296–308. [aJRA]CrossRefGoogle Scholar
Baron, J. (1985) Rationality and intelligence. Cambridge University Press. [jB]CrossRefGoogle Scholar
Baron, J. (1988) Thinking and deciding. Cambridge University Press. [JB]Google Scholar
Baron, J. (1990) Harmful heuristics and the improvement of thinking. In: Developmental perspectives on teaching and learning thinking skills, ed. Kuhn, D.. Karger. [ JB]Google Scholar
Baron, J., Badgio, P. & Gaskins, I. W. (1986) Cognitive style and its improvement: A normative approach. In: Advances in the psychology of human intelligence, vol. 3, ed. Sternberg, R. J.. Erlbaum. [JB]Google Scholar
Baron, J., Badgio, P. & Ritov, Y. (in press) Departures from optimal stopping in an anagram task. Journal of Mathematical Psychology. [JB]Google Scholar
Baum, W. M. (1974) On two types of deviation from the matching law: Bias and undermatching. Journal of the Experimental Analysis of Behavior 22:231–42. [HR]CrossRefGoogle ScholarPubMed
Bellman, R. (1961) Adaptive control processes: A guided tour. Princeton University Press. [GCA]CrossRefGoogle Scholar
Benkherouf, L. & Bather, J. A. (1988) Oil exploration: Sequential decisions in the face of uncertainty. Journal of Applied Probability 25:529“43. [WS]CrossRefGoogle Scholar
Berger, J. O. (1985) Statistical decision theory and Bayesian analyses. Springer-Verlag. [aJRA]CrossRefGoogle Scholar
Bernard, C. (1865) Introduction a I'etude de la medicine experimentale (2nd ed., 1867). Emile Martinet. [SLS]Google Scholar
Bickhard, M. H. (1980) Cognition, convention, and communication. Praeger. [RLC]Google Scholar
Bickhard, M. H. (1987) The social nature of the functional nature of language. In: Social and functional approaches to language and thought, ed. Hickmann, M.. Academic Press. [RLC]Google Scholar
Bickhard, M. H. (in press a) The import of Fodor's anticonstructivist arguments. In: Epistemological foundations of mathematical experience, ed. Steffe, L. P.. Springer. [RLC]Google Scholar
Bickhard, M. H. (in press b) How does the environment affect the person? In: Children's development within social contexts, ed. Winegar, L. T. & Valsiner, J.. Erlbaum.[RLC]Google Scholar
Bickhard, M. H. & Campbell, R. L. (1989) Interactivism and genetic epistemology. Archives de Psychologic 57:99–121. [RLC]Google Scholar
Bickhard, M. H. & Richie, D. M. (1983) On the nature of representation: A case study of James J. Gibsons theory of perception. Praeger. [RLC]Google Scholar
Birnbaum, M. H. (1983) Base rates in Bayesian inference: Signal detection analysis of the cab problem. American Journal of Psychology 96:85–94. [GG]CrossRefGoogle Scholar
Box, G. E. P. & Tiao, G. C. (1973) Bayesian inference in statistical analysis. Addison-Wesley. [rJRA]Google Scholar
Boyd, R. & Richerson, P. J. (1985) Culture and the evolutionary process. University of Chicago Press. [PG-S]Google Scholar
Brehmer, B. & Joyce, C. R. B., eds. (1988) Human judgment: The SJT view. North-Holland. [RH]Google Scholar
Broca, P. P. (1861) Nouvelle observation d'aphemie produite par une lesion de la partie posterieure des deuxieme et troisieme circonvolutions frontales. Bulletin de la Societe” Anatomique de Paris 6:398–407. [SLS]Google Scholar
Broemeling, L. D. (1985) Bayesian analysis of linear models. Marcel Dekker. [RAMG]Google Scholar
Brooks, L. (1978) Nonanalytic concept formation and memory for instances. In: Cognition and categorization, ed. Rosch, E. & Lloyd, B. B.. Erlbaum. [aJRA]Google Scholar
Brooks, R. (1987) Intelligence without representation. MIT AI Report. [RLC]Google Scholar
Brunswik, E. (1934) Wahrnehmung und Gegenstandswelt: Grundlegung einer Psychologic vom Gegenstand her (Perception and the world of objects: The foundations of a psychology in terms of objects). Deuticke. [RH]Google Scholar
Brunswik, E. (1943) Organismic achievement and environmental probability. Psychological Review 50:255–72. [RH]CrossRefGoogle Scholar
Brunswik, E. (1956) Perception and the representative design of psychological experiments. University of California Press. [aJRA, RH]CrossRefGoogle Scholar
Brunswik, E. (1964) Scope and aspects of the cognitive problem. In: Contemporary approaches to cognition, ed. Bruner, J. S. et al. Harvard University Press. [GG]Google Scholar
Buffart, H. F. J. M. & Geissler, H. G. (1983) Task-dependent representation of categories and memory-guided inference during classification. In: Trends in mathematical psychology, ed. Degreef, E. & van Buggenhaut, J.. North Holland. [H-GG]Google Scholar
Burrell, Q. L. (1980) A simple stochastic model for library loans. Journal of Documentation 36:115–32. [aJRA, GMB, WS]CrossRefGoogle Scholar
Burrell, Q. L. (1985) A note on aging on a library circulation model. Journal of Documentation 41:100–15. [GMB]CrossRefGoogle Scholar
Burrell, Q. L. & Cane, V. R. (1982) The analysis of library data. Journal of the Royal Statistical Society Series A (145):439–71. [aJRA]CrossRefGoogle Scholar
Bylander, T., Allemang, D., Tanner, M. & Josephson, J. (1989) Some results concerning the computational complexity of abduction. Proceedings of the First International Conference on Principles of Knowledge Representation and Reasoning, Toronto. [JKT]Google Scholar
Camerer, C., Loewenstein, G. & Weber, M. (1989) The curse of knowledge in economic settings: An experimental analysis. Journal of Political Economy 97:1232–54. [JB]CrossRefGoogle Scholar
Campbell, R. L. & Bickhard, M. H. (1986) Knowing levels and developmental stages. Karger. [RLC]Google Scholar
Campbell, R. L. & Bickhard, M. H. (1987) A deconstruction of Fodor's anticonstructivism. Human Development 30:48–59. [RLC]CrossRefGoogle Scholar
Chapman, G. B. (1990) Models of contingency judgment. Ph.D. thesis, Department of Psychology, University of Pennsylvania. [JB]Google Scholar
Chapman, L. J. & Chapman, J. P. (1967) Genesis of popular but erroneous psychodiagnostic observations. Journal of Abnormal Psychology 72:193–204. [JB]CrossRefGoogle Scholar
Chapman, L. J. & Chapman, J. P. (1969) Illusory correlation as an obstacle to the use of valid psychodiagnostic signs. Journal of Abnormal Psychology 74:271–80. [JB]CrossRefGoogle Scholar
Cheeseman, P., Kelly, J., Self, M., Stutz, J., Taylor, W. & Freeman, D. (1988) A Bayesian classification system. In: Proceedings of the Fifth International Conference on Machine Learning, San Mateo, CA. [aJRA]CrossRefGoogle Scholar
Cheng, P. & Holyoak, K. (1985) Pragmatic reasoning schemas. Cognitive Psychology 17:391–416. [GG]CrossRefGoogle ScholarPubMed
Chow, C. & Scheduler, Z. (1985) On stopping rules in proofreading. Journal of Applied Probability 22:971–77. [WS]CrossRefGoogle Scholar
Clark, C. (1991) Modeling behavioral adaptations. Behavioral and Brain Sciences 14(1):85–118. [BWD]CrossRefGoogle Scholar
Cohen, L. J. (1981) Can human irrationality be experimentally demonstrated? Behavioral and Brain Sciences 4:317–70. [PS]CrossRefGoogle Scholar
Cohen, M. M. & Massaro, D. W. (in press) On the similarity of categorization models. In: Probabilistic multidimensional models of perception and cognition, ed. Ashby, F. G.. Erlbaum. [DWM]Google Scholar
Corcos, D. M.Gottlieb, G. L. & Agarwal, G. C. (1988) Accuracy constraints upon rapid elbow movements. Journal of Motor Behavior 20:255–72. [GCA]CrossRefGoogle ScholarPubMed
Corter, J. E. or Gluck, M. A. (1985) The pragmatics of semantics: Information, communication and levels of abstraction. Paper presented at meeting of the Society for Philosophy and Psychology, University of Toronto. [JEC] (submitted) Explaining basic categories: Feature predictability and information. [JEC]Google Scholar
Cosmides, L. (1989) The logic of social exchange: Has natural selection shaped how humans reason? Cognition 31:187–276. [GG]CrossRefGoogle ScholarPubMed
Crocker, J. (1981) Judgment of covariation by social perceivers. Psychological Bulletin 90:272–92. [aJRA]CrossRefGoogle Scholar
deGroot, M. H. Groot, M. H. (1970) Optimal statistical decisions. McGraw-Hill. [rJRA, RAMG]Google Scholar
Doyle, R. (1989) Reasoning about hidden mechanisms. Proceedings of the International Joint Conference on Artificial Intelligence. [TRS]Google Scholar
Dupré, J. (1987) The latest on the best. MIT Press. [aJRA]Google Scholar
Edelman, G. M. (1987) Neural Darwinism. Basic Books. [H-GG]Google Scholar
Einhorn, H. J. & Hogarth, R. M. (1986) Judging probable cause. Psychological Bulletin 99:3–19. [aJRA]CrossRefGoogle Scholar
Evans, J. St. B. T. (1989) Bias in human reasoning: Causes and consequences. Erlbaum. [JSBTE]Google Scholar
Fantino, E. & Abarca, N. (1985) Choice, optimal foraging and the delay-reduction hypothesis. Behavioral and Brain Sciences 8:315–30. [aJRA]CrossRefGoogle Scholar
Feller, W. (1968) An introduction to probability theory and its applications, 3rd ed., vol. 1. Wiley. [WS]Google Scholar
Fisher, D. H. (1987) Knowledge acquisition via incremental conceptual clustering. Machine Learning 2:139–72. [aJRA]CrossRefGoogle Scholar
Fisher, K. A. (1936) Multiple measurements of taxonomic problems. Annals of Eugenics 7:179–88. [rJRA]CrossRefGoogle Scholar
Fitts, P. M. (1954) The information capacity of the human motor system in controlling the amplitude of movement. Journal of Experimental Psychology 47:381–91. [GCA]CrossRefGoogle ScholarPubMed
Fitts, P. M. & Peterson, J. R. (1964) Information capacity of discrete motor responses. Journal of Experimental Psychology 67:102–12. [GCA]CrossRefGoogle ScholarPubMed
Fodor, J. (1975) The language of mind. Crowell. [RLC]Google Scholar
Fodor, J. (1980) Fixation of belief and concept acquisition. In: Language and learning: The debate between Jean Piaget and Noam Chomsky, ed. Piattelli-Palmarini, M.. Harvard University Press. [RLC]Google Scholar
Fodor, J. (1981) The present status of the innareness controversy. In: Representations, ed. Fodor, J.. MIT Press. [RLC]Google Scholar
Freyd, J. J. (1982) Shareability: The social psychology of epistemology. Cognitive Science 7:191–210. [JEC]Google Scholar
Fried, L. S. & Holyoak, K. J. (1984) Induction of category distributions: A framework for classification learning. Journal of Experimental Psychology: Learning, Memory, and Cognition 10:234–57. [aJRA]Google ScholarPubMed
Funder, D. C. (1987) Errors and mistakes: Evaluating the accuracy of social judgment. Psychological Bulletin 101:75–90. [rJRA, JB]CrossRefGoogle ScholarPubMed
Gal, I. (1990) Understanding repeated choices under uncertainty. Ph.D. thesis, Department of Psychology, University of Pennsylvania. [JB]Google Scholar
Geissler, H. G. (1970) Calibration law and space orientation (in German). Unpub. doctoral dissertation, Humboldt University, Berlin. [H-GG]Google Scholar
Geissler, H. G. (1976) Internal representation of external states: Aspects of an indirect validation approach to psychophysics. In: Advances in psychophysics, ed. Geissler, H. G. & Zabrodin, Yu. M.. Deutscher Verlag der Wissenschaften. [H-GG]Google Scholar
Geissler, H. G. (1980) Perceptual representation of information: Dynamic frames of references in judgment and recognition. In: Psychological research, Humboldt University 1960–1980, ed. Klix, F. & Krause, B.. Deutscher Verlag der Wissenschaften. [H-GG]Google Scholar
Geissler, H. G. (1983) Physical correlate theory versus indirect calibration approach. Behavioral and Brain Sciences 2:316–18. [H-GG]CrossRefGoogle Scholar
Geissler, H. G. (1987) The temporal architecture of central information processing: Evidence for a tentative time-quantum model. Psychological Research 49:99–106. [H-GG]CrossRefGoogle Scholar
Geissler, H. G. (1991) New magical numbers in mental activity? On a taxonomic system for critical time periods. In: Cognition, information processing and psychophysics: Basic issues, ed. Geissler, H. G.Link, S. W. & Townsend, J. T.. Erlbaum [H-GG].Google Scholar
Geissler, H. G. & Buffart, H. F. M. J. (1985) Task dependency and quantized processing in classification. In: Cognition, information processing and motivation, selected revised papers, vol. 3, ed. d'Ydewalle, G.. North-Holland. [H-GG]Google Scholar
Geissler, H. G. & Puffe, M. (1983) The inferential basis of classification: From perceptual to memory code systems. In: Modern issues in perception, ed. Geissler, H. G., Buffart, H. F. M. J., Leeuwenberg, E. L. J. & Sarris, V.. Deutscher Verlag der Wissenschaften. North-Holland. [H-GG]Google Scholar
Geissler, H. G., Klox, F. & Scheidereiter, U. (1978) Visual recognition of serial structure: Evidence of a two-stage scanning model. In: Formal theories of perception, ed. Leeuwenberg, E. L. J. & Buffart, H. F. J. M.. Wiley. [H-GG]Google Scholar
Gelfand, A. E. & Smith, A. F. M. (1990) Sampling-based approaches to calculating marginal densities. Journal of the American Statistical Association 85:398–409. [rJRA]CrossRefGoogle Scholar
Gibbon, J. (1986) The structure of subjective time: How time flies. In: The psychology of learning and motivation, vol. 20, ed. Bower, G. H.. Academic Press. [HR]Google Scholar
Gibson, J. J. (1966) The senses considered as perceptual systems. Houghton Mifflin. [aJRA]Google Scholar
Gibson, J. J. (1979) The ecological approach to visual perception. Houghton Mifflin. [aJRA]Google Scholar
Gigerenzer, G. (1991) From tools to theories. A heuristic of discovery in cognitive psychology. Psychological Review 98 (in press). [GG]CrossRefGoogle Scholar
Gigerenzer, G. & Murray, D. J. (1987) Cognition as intuitive statistics. Erlbaum. [GG]Google Scholar
Gigerenzer, G., Hell, W. & Blank, H. (1988) Presentation and content: The use of base rates as a continuous variable. Journal of Experimental Psychology: Human Perception and Performance 14:513–25. [DWM]Google Scholar
Gillund, G. & Shiffrin, R. M. (1984) A retrieval model for both recognition and recall. Psychological Review 91:1–67. [aJRA]CrossRefGoogle ScholarPubMed
Glenberg, A. M. (1976) Monotonic and nonmonotonic lag effects in paired-associate and recognition memory paradigms. Journal of Verbal Learning and Verbal Behavior 15:1–16. [aJRA]CrossRefGoogle Scholar
Gluck, M. A. & Bower, G. H. (1988) From conditioning to category learning:An adaptive network model. Journal of Experimental Psychology: General 8:37–50. [aJRA]Google Scholar
Gluck, M. A. & Corter, J. E. (1985) Information, uncertainty, and the utilityof categories. In: Proceedings of the Seventh Annual Conference of the Cognitive Science Society. Erlbaum. [JEC]Google Scholar
Godbeer, G. (1987) The computational complexity of the stable configuration problem for connectionist models. M.S. thesis, Department of Computer Science, University of Toronto, September (Tech. Report 208/88). [JKT]Google Scholar
Gottlieb, G. L., Corcos, D. M. & Agarwal, G. C. (1989) Strategies for the control of voluntary movements with one mechanical degree of freedom. Behavioral and Brain Sciences 12:189–250. [GCA]CrossRefGoogle Scholar
Gould, S. J. (1986) Evolution and the triumph of homology, or why historymatters. American Scientist 74:60–69. [DWM]Google Scholar
Gould, S. J. & Lewontin, R. C. (1979) The spandrels of San Marco and the Panglossian paradigm: A critique of the adaptionist program. Proceedings of the Royal Society of London 205:581–98. [aJRA]Google Scholar
Gould, S. J. & Lewontin, R. C. (1979) The spandrels of San Marco and the Panglossian paradigm: A critique of the adaptionist program. Reprinted In: Conceptual issues in evolutionary biology: An anthology, ed. Sober, E.. MIT Press. (1984). [PG-S]Google Scholar
Greiner, R. (1990) Finding the optimal derivation strategy in a redundantknowledge base. Artificial Intelligence (in press). [JKT]Google Scholar
Grossberg, S., ed. (1988) Competitive learning: From interactive activation to adaptive resonance. In: Neural networks and natural intelligence. MIT Press. [H-GG]CrossRefGoogle Scholar
Hammond, K. R. (1955) Probabilistic functioning and the clinical method. Psychological Review 62:255–62. [RH]CrossRefGoogle ScholarPubMed
Hammond, K. R. (1988) Judgement and decision making in dynamic tasks. Information and Decision Technologies 14:3–14. [RH]Google Scholar
Hamad, S. (1989) The symbol grounding problem. Physica D 42:335–46. [RLC]Google Scholar
Hayes-Roth, B. & Hayes-Roth, F. (1977) Concept learning and therecognition and classification of exemplars. Journal of Verbal Learning and Verbal Behavior 16:321–38. [aJRA]CrossRefGoogle Scholar
Herrnstein, R. J. (1990) Rational choice theory: Necessary but not sufficient. American Psychologist 45 (3):356–67. [aJRA]CrossRefGoogle Scholar
Herrnstein, R. J. & Vaughan, W. Jr. (1980) Melioration and behavioral allocation. In: Limits to action: The allocation of individual behavior, ed. Staddon, J. E. R.. Academic Press. [aJRAjGoogle Scholar
Heyman, G. M. & Herrnstein, R. J. (1986) More on concurrent interval-ratio schedules: A replication and review. Journal of the Experimental Analysis of Behavior 46:331–51. [EF]CrossRefGoogle ScholarPubMed
Hoffman, J. … Ziessler, C. (1983) Objectidentifikation in kunstlichen Begriffshierarchien. Zeitschrift fur Psychologie 194:135–67. [aJRA, H-GG]Google Scholar
Homa, D. & Cultice, J. (1984) Role of feedback, category size, and stimulus distortion in the acquisition and utilization of ill-defined categories. Journal of Experimental Psychology: Learning, Memory, and Cognition 10:83–94. [aJRA]Google Scholar
Houston, A. I. & McNamara, J. M. (1988) A framework for the functionalanalyses of behaviour. Behavioral and Brain Sciences 11:117–63. [aJRA]CrossRefGoogle Scholar
Jeffrey, R. (1987) Risk and human rationality. Monist 70:223–36. [GG]CrossRefGoogle Scholar
Johnson-Laird, P. N. & Byrne, R. (in press) Deduction. Hove & London: Erlbaum. [JSBTE]Google Scholar
Jones, G. V. (1983) Identifying basic categories. Psychological Bulletin 92:174–77. [JEC]Google Scholar
Just, M. A. & Carpenter, P. A. (1980) A theory of reading: Eye fixations tocomprehension. Psychological Review 87:329–54. [SLS]CrossRefGoogle Scholar
Kahneman, D. & O'Curry, S. (1988) Surprise as an indication for spontaneous categorization. Presented at the 29th Annual Meeting of the Psychonomic Society, November 10–12. [aJRA]Google Scholar
Kahneman, D. & Tversky, A. (1972) Subjective probability: A judgment of representativeness. Cognitive Psychology 3:430–54. [JB]CrossRefGoogle Scholar
Kahneman, D. & Tversky, A. (1973) On the psychology of prediction. Psychological Review 80:237–51. [ES]CrossRefGoogle Scholar
Kahneman, D. & Tversky, A. (1979) Prospect theory: An analysis of decision under risk. Econometrica 47:263–91. [JB, PS]CrossRefGoogle Scholar
Kahneman, D. & Tversky, A. (1984) Choices, values and frames. American Psychologist 39:341–50. [aJRA, ES]CrossRefGoogle Scholar
Kahneman, D., Slovic, P. & Tversky, A. (1982) Judgment under uncertainty: Heuristics and biases. Cambridge University Press. [JSBTE]CrossRefGoogle Scholar
Kautz, H. & Selman, B. (in press) Hard problems for simple default logics. Artificial Intelligence. [JKT]Google Scholar
Kettlewell, P. (1973) The evolution of melanism. Oxford University Press (Oxford). [aJRA]Google Scholar
Kintsch, W. (1970) Models for free recall and recognition. In: Models of human memory, ed. Norman, D. A.. Academic Press. [aJRA]Google Scholar
Kirousis, L. & Papadimitriou, C. (1985) The complexity of recognizing polyhedral scenes. Proceedings of the 26th Annual Symposium on Foundations of Computer Science, October, Portland, OR. [JKT]CrossRefGoogle Scholar
Knetsch, J. L. & Sinden, J. A. (1984) Willingness to pay and compensation: Experimental evidence of an unexpected disparity in measures of value. Quarterly Journal of Economics 99:508–22. [JB]CrossRefGoogle Scholar
Kotovsky, K., Hayes, J. R. & Simon, H. A. (1985) Why are some problemshard? Evidence from Tower of Hanoi. Cognitive Psychology 17:248–94. [aJRA]CrossRefGoogle Scholar
Kuhn, D. (1989) Children and adults as intuitive scientists. Psychological Review 96:674–89. [TRS]CrossRefGoogle ScholarPubMed
Kuhn, D. (in press) The skills of argument. Cambridge University Press. [JB]Google Scholar
Kuhn, D., Amsel, E. & O'Loughlin, M. (1988) The development of scientific thinking skills. Academic Press. [JB]Google Scholar
Kunda, Z., & Nisbett, R. E. (1986) The psychometrics of everyday life. Cognitive Psychology 18:195–224. [KJH]CrossRefGoogle ScholarPubMed
Kyburg, H. E. Jr. (1983) Rational belief. Behavioral and Brain Sciences 6:231–73. [PS]CrossRefGoogle Scholar
Langley, P., Bradshaw, G. L. & Simon, H. A. (1983) Rediscovering chemistrywith the Bacon system. In: Machine learning: An artificial approach, ed. Michalski, R. S., Carbonell, J. G. & Mitchell, T. M.. Tioga. [SLS]Google Scholar
Larrick, R. P., Morgan, J. N. & Nisbett, R. E. (1990) Teaching the use ofcost-benefit reasoning in everyday life. Psychological Science 1:362–70. [JB]CrossRefGoogle Scholar
Larrick, R. P., Nisbett, R. E. & Morgan, J. N. (1990) Who uses cost-benefit reasoning? Unpub. manuscript, University of Michigan, Ann Arbor, MI. [JB]Google Scholar
Lebowitz, M. (1987) Experiments with incremental concept formation: UNIMEM. Machine Learning 2:103–38. [aJRA]CrossRefGoogle Scholar
Lee, P. M. (1989) Bayesian statistics. Oxford University Press. [rJRA]Google Scholar
Leeuwenberg, E. L. J. & Buffart, H. F. M. J. (1983) An outline of codingtheory. Summary of some related experiments. In: Modern issues in perception, ed. Geissler, H. G., Buffart, H. F. M. J., Leeuwenberg, E. L. J. & Sarris, V.. Deutscher Verlag der Wissenschaften. North-Holland. [H-GG]Google Scholar
Lewontin, R. C. (1990) The evolution of cognition. In: An invitation to cognitive science, vol. 3, ed. Osherson, D. & Smith, E.. MIT Press. [ES]Google Scholar
Lichtenstein, S., Fischhoff, B. & Phillips, B. (1982) Calibration of probabilities: The state of the art to 1980. In: Judgment under uncertainty: Heuristics and biases, ed. Kahneman, D., Slovic, P. & Tversky, A.. Cambridge University Press. [JB]Google Scholar
Logsdon, J. B. (1990) Principles of optimum control of rapid human limbmovements. M.S. thesis, Department of Electrical Engineering and Computer Science, University of Illinois at Chicago. [GCA]Google Scholar
Luce, R. D. (1986) Response times. Oxford University Press. [WS]Google Scholar
Macphail, E. M. (1987) The comparative psychology of intelligence. Behavioral and Brain Sciences 10:645–95. [RdS]CrossRefGoogle Scholar
Mandler, J. M., Bauer, P. J. & McDonough, L. (1988) Differentiating globalcategories. Presented at the 29th Annual Meeting of the Psychonomic Society, November 10–12. [aJRA]Google Scholar
Marr, D. (1982) Vision. W. H. Freeman. [aJRA, SLS, TZ]Google Scholar
Marr, D. & Poggio, T. (1977) A theory of human stereo vision. Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Technical Report AI Memo 451. [SLS]Google Scholar
Massaro, D. W. (1987) Speech perception by ear and eye: A paradigm for psychological inquiry. Erlbaum. [DWM]Google Scholar
Massaro, D. W. (1989) Testing between the TRACE model and the fuzzy logical model ofperception. Cognitive Psychology 21:398–421. [DWM]CrossRefGoogle Scholar
Massaro, D. W. & Friedman, D. (1990) Models of integration given multiplesources of information. Psychological Review 97:225–52. [DWM]CrossRefGoogle Scholar
Mayr, E. (1983) How to carry out the adaptionist program? American Naturalist 121:324–34. [aJRA]CrossRefGoogle Scholar
McNeil, B. J., Pauker, S. G., Sox, H. C. & Tversky, A. (1982) On theelicitation of preferences for alternative therapies. New England Journal of Medicine 306:1259–62. [ES]CrossRefGoogle ScholarPubMed
Medin, D. L. (1983) Structural principles of categorization. In: Interaction: Perception, development and cognition, ed. Shepp, B. & Tighe, T.. Erlbaum. [JEC]Google Scholar
Medin, D. L. & Edelson, S. M. (1988) Problem structure and the use ofbase-rate information from experience. Journal of Experimental Psychology: General 117:68–85. [aJRA]CrossRefGoogle ScholarPubMed
Medin, D. L. & Schaffer, M. M. (1978) Context theory of classification learning. Psychological Review 85:207–38. [aJRA]CrossRefGoogle Scholar
Medin, D. L., Altom, M. W., Edelson, S. M. & Freko, D. (1982) Correlated symptoms and simulated medical classification. Journal of Experimental Psychology: Learning, Memory, and Cognition 8:37–50. [aJRA]Google ScholarPubMed
Meltzer, H. Y. & Stahl, S. M. (1976) The dopamine hypothesis of schizophrenia: A review. Schizophrenia Bulletin 2: 19–76. [SLS]CrossRefGoogle ScholarPubMed
Meyer, D. E. & Schvaneveldt, R. W. (1971) Facilitation in recognizing pairsof words: Evidence of a dependence between retrieval operations. Journal of Experimental Psychology 90:227–34. [aJRA]CrossRefGoogle Scholar
Meyer, D. E., Smith, J. E. K. & Wright, C. E. (1982) Models for the speedand accuracy of aimed movements. Psychological Review 89:449–82. [GCA]CrossRefGoogle Scholar
Meyer, D. E., Abrams, R. A., Kornblum, S., Wright, C. E. & Smith, J. E. K. (1988) Optimality in human motor performance: Ideal control of rapidaimed movements. Psychological Review 95:340–70. [GCA]CrossRefGoogle Scholar
Michotte, A. (1946) La perception de la causalité. Vrin. [rJRA]Google Scholar
Moore, E. F. (1956) Gedanken-experiments on sequential machines. In: Automata studies, ed. Shannon, C. E. & McCarthy, J.. Princeton University Press. [DWM]Google Scholar
Mpitsos, G. J., Burton, R. M. & Creech, H. C. (1988) Connection is networks learn to transmit chaos. Brain Research Bulletin 21:539–46. [RAMG]CrossRefGoogle Scholar
Murphy, G. L. & Medin, D. L. (1985) The role of theories in conceptual coherence. Psychological Review 92:293–316. [JEC]CrossRefGoogle ScholarPubMed
Murphy, G. L. & Smith, E. E. (1982) Basic level superiority in picturecategorization. Journal of Verbal Learning and Verbal Behavior 21:1–20. [aJRA]CrossRefGoogle Scholar
Neches, R., Langley, P. & Klahr, D. (1987) Production systems, learning, and development. In: Production system models of learning and development, ed. Klahr, D., Langley, P. & Neches, R.. MIT Press. [RLC]Google Scholar
Neely, J. H. (1977) Semantic priming and retrieval from lexical memory: Roles of in hibitionless spreading activation and limited-capacity attention. Journal of Experimental Psychology: General 106:226–54. [aJRA]CrossRefGoogle Scholar
Newell, A. (1980) Physical symbol systems. Cognitive Science 4:135–83. [RLC]Google Scholar
Newell, A. (1982) The knowledge level. Artificial Intelligence 18:87–127. [BC]CrossRefGoogle Scholar
Newell, A. & Rosenbloom, P. (1981) Mechanisms of skill acquisition and thelaw of practice. In: Cognitive skills and their acquisition, ed. Anderson, J. R.. Erlbaum. [aJRA]Google Scholar
Newell, A. & Simon, H. A. (1972) Human problem solving. Prentice Hall. [JSBTE]Google Scholar
Nisbett, R. E. & Ross, L. (1980) Human inference: Strategies and shortcomings of social judgment. Prentice-Hall. [aJRA]Google Scholar
Nisbett, R. E., Fong, G. T., Lehman, D. R. & Cheng, P. W. (1987) Teaching reasoning. Science 238:625–31. [JB]CrossRefGoogle ScholarPubMed
Peterson, C. R. & Beach, L. R. (1967) Man as an intuitive statistician. Psychological Bulletin 68:29–46. [JB, JSBTE]CrossRefGoogle Scholar
Peterson, C. R. & Uhela, Z. J. (1964) Uncertainty, inference difficulty, andprobability learning. Journal of Experimental Psychology 67:523–30. [JB]CrossRefGoogle ScholarPubMed
Petruccelli, J. D. (1981) Best-choice problems involving uncertainty ofselection and recall of observations. Journal of Applied Probability 18:415–25. [WS]CrossRefGoogle Scholar
Piaget, J. (1970) Genetic epistemology. Columbia University Press. [RLC]CrossRefGoogle Scholar
Polya, G. (1954) Mathematics and plausible reasoning. Vol. 2: Patterns of plausible inference. Princeton University Press. [PS]Google Scholar
Posner, M. I. & Keele, S. W. (1968) On the genesis of abstract ideas. Journal of Experimental Psychology 77:353–63. [aJRA]CrossRefGoogle ScholarPubMed
Prade, H. (1985) A computational approach to approximate and plausible reasoning with applications to expert systems. IEEE Transactions on Pattern Analysis Machine Intelligence 7:260–82. [PS]CrossRefGoogle ScholarPubMed
Pylyshyn, Z. W. (1984) Computation and cognition. MIT Press. [RLC]Google Scholar
Rachlin, H. (1989) Judgment, decision, and choice: A cognitive/behavioral synthesis. W. H. Freeman. [EF, HR]Google Scholar
Rachlin, H., Battalio, R. C., Kagel, J. H. & Green, L. (1981) Maximization theory in behavioral psychology. Behavioral and Brain Sciences 4:371–88. [aJRA]CrossRefGoogle Scholar
Redelmeier, D. A. & Tversky, A. (1990) The aggregate/individualdiscrepancy: Contrasting perspectives in medical care. New England Journal of Medicine (in press). [ES]Google Scholar
Reed, S. K. (1972) Pattern recognition and categorization. Cognitive Psychology 3:382–407. [aJRA]CrossRefGoogle Scholar
Riefer, D. M. & Batchelder, W. H. (1988) Multinomial modeling and the measurement of cognitive processes. Psychological Review 95:318–39. [WS]CrossRefGoogle Scholar
Rosch, E. (1978) Principles of categorization. In: Cognition and categorization, ed. Rosch, E. & Lloyd, B. B.. Erlbaum. [GG]Google Scholar
Rosch, E., Mervis, C. B., Gray, W., Johnson, D. & Boyes-Braem, P. (1976) Basic objects in natural categories. Cognitive Psychology 7:573–605. [aJRA, JEC]CrossRefGoogle Scholar
Rosenbloom, P. S., Laird, J. E. & Newell, A. (1987) SOAR: An architecturefor general intelligence. Artificial Intelligence 33:1–64. [BC]Google Scholar
Rumelhart, D. E. & McClelland, J. L. (1986) Parallel distributed processing: Explorations in the microstructure of cognition. Vol. 1: Foundations. MIT Press. [SLS]CrossRefGoogle Scholar
Rumelhart, D. E., Hinton, G. E. & Williams, R. J. (1986) Learninginternal representations by error propagation. In: Parallel distributed processing, vol. 1., ed. Rumelhart, D. E. & McClelland, J. L.. MIT Press. [aJRA]CrossRefGoogle Scholar
Rumelhart, D. E.McClelland, J. L. & the PDF Research Group (1986) Parallel distributed processing: Explorations in the microstructure of cognition, vols. 1–2. MIT Press. [KJH]CrossRefGoogle Scholar
Russell, S. J. (1986) A quantitative analysis of analogy by similarity. In: Proceedings of the National Conference on Artificial Intelligence, (AAAI). [aJRA]Google Scholar
Salton, G. & McGill, M. J. (1983) Introduction to modern information Philadelphia, PA. American Association for Artificial Intelligence retrieval. McGraw-Hill. [a]RA]Google Scholar
Satyanarayanan, M. (1981) A study of file sizes and functional lifetimes. In: Proceedings of the Eighth Symposium on Operating Systems Principles, Asilomar, CA, December. [aJRA]CrossRefGoogle Scholar
Schultz, T. R. (1982) Rules for causal attribution. Monographs of the Society for Research in Child Development 47(1, Serial No. 194). [aJRA]Google Scholar
Schustack, M. W. & Sternberg, R. J. (1981) Evaluation of evidence in causal inference. Journal of Experimental Psychology: General 110:101–20. [aJRA, TRS]CrossRefGoogle Scholar
Schwarz, W. (1989) The generalized Bouman-van der Velden quantum coincidence detector. Biological Cybernetics 61:315–18. [WS]CrossRefGoogle Scholar
Schwarz, W. (1990) Stochastic accumulation of information in discrete time: Comparing exact results and Wald approximations. Journal of Mathematical Psychology 34:229–36. [WS]CrossRefGoogle Scholar
Selman, B. & Kautz, H. (1990) Model-preference default theories. Artificial Intelligence 45:287–322. [JKT]CrossRefGoogle Scholar
Selman, B. & Levesque, H. (1989a) Abductive and default reasoning: A computational core. Proceedings of the Eighth National Conference on Artificial Intelligence, Boston, MA. [JKT]Google Scholar
Selman, B. & Levesque, H. (1989b) The tractability of path-based inheritance. Proceedings of the Eleventh International Joint Conference on Artificial Intelligence, Detroit, August. [JKT]Google Scholar
Shackle, G. L. S. (1949) Expectation in economics. Cambridge University Press (Cambridge). [PS]Google Scholar
Shafir, E. B., Osherson, D. N. & Smith, E. E. (1989) An advantage model of choice. Journal of Behavioral Decision Making 2:1–23. [ES]CrossRefGoogle Scholar
Shepard, R. N. (1987) Towards a universal law of generalization for psychological science. Science 237:1317–23. [aJRA]CrossRefGoogle Scholar
Shepard, R. N. (1989) A law of generalization and connectionist learning. Plenary address to the Cognitive Science Society, Ann Arbor, MI, August 18. [aJRA]Google Scholar
Shimp, C. P. (1966) Probabilistically reinforced choice behavior in pigeons. Journal of the Experimental Analysis of Behavior 9:443–55. [aJRA]CrossRefGoogle ScholarPubMed
Shultz, T. R. & Ravinsky, F. (1977) Similarity as a principle of causal inference. Child Development 48:1552–58. [TRS]CrossRefGoogle Scholar
Simon, H. A. (1955a) A behavioral model of rational choice. Quarterly Journal of Economics 69:99–118. [aJRA, GMB]CrossRefGoogle Scholar
Simon, H. A. (1955b) On a class of skew distribution functions. Biometrika 52:425–40. [rJRA]CrossRefGoogle Scholar
Simon, H. A. (1982) The sciences of the artificial, 2nd ed. MIT Press. [BC]Google Scholar
Slovic, P. & Lichtenstein, S. (1971) Comparison of Bayesian and regression approaches to the study of information processing in judgment. Organizational Behavior and Human Performance 6:649–744. [RH]CrossRefGoogle Scholar
Slovic, P., Fischhoff, B. & Lichtenstein, S. (1977) Behavioral decision theory. Annual Review of Psychology 228:1–39. [JSBTE]CrossRefGoogle Scholar
Slovic, P., Fischhoff, B. & Lichtenstein, S. (1978) Accident probabilities and seat belt usage: A psychological perspective. Accident Analysis and Prevention 10:281–85. [ES]CrossRefGoogle Scholar
Slovic, P., Fischhoff, B. & Lichtenstein, S. (1982) Response mode, framing and information-processing effects in risk assessment. In: New directions for methodology of social and behavioral science: No. 11. Question framing and response consistency, ed. Hogarth, R.. Jossey-Bass. [ES]Google Scholar
Solnick, J. V., Kanneberg, C. H., Eckerman, D. A. & Waller, M. B. (1980) An experimental analysis of impulsivity and impulse control in humans. Learning and Motivation 11:61–77. [JB]CrossRefGoogle Scholar
Spall, J. C. (1988) Bayesian analysis of time series and dynamic models. Marcel Dekker. [RAMG]Google Scholar
Staddon, J. E. R. (1987) Optimality theory and behavior. In: The latest on the best: Essays on evolution and optimality, ed. Dupre, J.. MIT Press. [aJRA, EF]Google Scholar
Stephens, D. W. & Krebs, J. R. (1986) Foraging theory. Princeton University Press. [arJRA]Google Scholar
Stolarz-Fantino, S. & Fantino, E. (1990) Cognition and behavior analysis: Areview of Rachlin's Judgment, decision and choice. Journal of the Experimental Analysis of Behavior 54:317–22. [EF]CrossRefGoogle Scholar
Stritter, E. (1977) File migration. Unpub. Ph.D. thesis (STAN-CS-77-594), Stanford University. [aJRA]Google Scholar
Suppes, P. (1984) Probabilistic metaphysics. Basil Blackwell. [aJRA]Google Scholar
Tanner, M. A. & Wong, W. H. (1987) The calculation of posteriordistributions by data augmentation. Journal of the American Statistical Association 82:528–40. [rJRA]CrossRefGoogle Scholar
Thagard, P. (1989) Explanatory coherence. Behavioral and Brain Sciences 12:435–67. [KJH]CrossRefGoogle Scholar
Thagard, P., Hoiyoak, K. J., Nelson, G. & Gochfeld, D. (1990) Analog retrieval by constraint satisfaction. Artificial Intelligence 46:259–310. [KJH]CrossRefGoogle Scholar
Thaler, R. H. (1980) Toward a positive theory of consumer choice. Journal of Economic Behavior and Organization 1:39–60. [ES]CrossRefGoogle Scholar
Tierney, L. & Kadane, J. B. (1986) Accurate approximations for posteriormoments and marginal destinies. Journal of the American Statistical Association 81:82–86. [rJRA]CrossRefGoogle Scholar
Townsend, J. T. (1971) A note on the identifiability of parallel and serial processes. Perception & Psychophysics 10:161–63. [WS]CrossRefGoogle Scholar
Townsend, J. T. & Ashby, F. G. (1983) Stochastic modeling of elemen'tary psychological processes. Cambridge University Press (Cambridge). [WS]Google Scholar
Tsotsos, J. (1989) The complexity of perceptual search tasks. Proceedings ofthe International Joint Conference on Artificial Intelligence, Detroit, August. [JKT]Google Scholar
Tsotsos, J. (1990) Analyzing vision at the complexity level. Behavioral and Brain Sciences 13(3):423–45. [JKT]CrossRefGoogle Scholar
Tsotsos, J. (submitted) Active vs. passive visual search: Which is more efficient? International Journal of Computer Vision. [JKT]Google Scholar
Tversky, A. & Kahneman, D. (1980) Causal schemas in judgment underuncertainty. In: Progress in social psychology, vol. 1, ed. Fishbein, M.. Erlbaum. [TRS]Google Scholar
Tsotsos, J. (1982) Evidential impact of base rates. In Judgment under uncertainty: Heuristics and biases, ed. Kahneman, D., Slovic, P. & Tversky, A.. Cambridge University Press. [EF]Google Scholar
Tsotsos, J. (1983) Extension versus intuitive reasoning: The conjunction fallacy in probability judgment. Psychological Review 90:293–315. [DWM]Google Scholar
Von Winterfeldt, D. & Edwards, W. (1986) Decision analysis and behavioural research. Cambridge University Press (Cambridge). [JSBTE]Google Scholar
Vorberg, D. (1977) On the equivalence of parallel and serial models ofinformation processing. Paper presented at the 10th Annual Mathematical Psychology Meeting, Los Angeles, CA. [WS]Google Scholar
Vorberg, D. & Ulrich, R. (1987) Random search with unequal search rates:Serial and parallel generalizations of McGill's model. Journal of Mathematical Psychology 31:1–23. [WS]CrossRefGoogle Scholar
Wasserman, E. A. (1990) Attribution of causality to common and distinctiveelements of compound stimuli. Psychological Science 1:298–302. [JB]CrossRefGoogle Scholar
White, K. G., McCarthy, D. & Fantino, E. (1989) Cognition and behavioranalysis. Journal of the Experimental Analysis of Behavior 52:197–98. [EF]CrossRefGoogle Scholar
Wickelgren, W. A. (1976) Memory storage dynamics. In: Handbook of learning and cognitive processes, ed. Estes, W. K.. Erlbaum. [aJRA]Google Scholar
Wilkie, D. R. (1954) Facts and theories about muscle. Progress in Biophysics and Biophysical Chemistry 4:288–324. [GCA]CrossRefGoogle Scholar
Williams, B. A. (1988) Reinforcement, choice, and response strength. In:Stevens's handbook of experimental psychology, ed. Atkinson, R. C., Herrnstein, R. J., Lindzey, G. & Luce, R. D.. Wiley. [aJRA]Google Scholar