Minds and Machines

, Volume 7, Issue 4, pp 553–569 | Cite as

Two Projects for Understanding the Mind: A Response to Morris and Richardson

  • Nick Chater
  • Martin Pickering
Article
  • 40 Downloads

Abstract

We respond to Morris and Richardson's (1995) claim that Pickering and Chater's (1995) arguments about the lack of a relation between cognitive science and folk psychology are flawed. We note that possible controversies about the appropriate uses for the two terms do not affect our arguments. We then address their claim that computational explanation of knowledge-rich processes has proved possible in the domains of problem solving, scientific discovery, and reasoning. We argue that, in all cases, computational explanation is only possible for aspects of those processes that do not make reference to general knowledge. We conclude that consideration of the issues raised by Morris and Richardson reinforces our original claim that there are two fundamentally distinct projects for understanding the mind, one based on justification, and the other on computational explanation, and that these apply to non-overlapping aspects of mental life.

Folk psychology cognitive science justifications causes computation knowledge-free knowledge-rich problem solving scientific discovery reasoning 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Aggleton, J.P. (1992), The Amygdala: Neurobiological Aspects of Emotion. Memory, and Mental Function. New York: Wiley-Liss.Google Scholar
  2. Agre, P. E. & Chapman, D. (1987), ‘Pengi: An implementation of a theory of activity’, Proceedings of the American Association for Artificial Intelligence, Seattle, PA, pp. 268-272.Google Scholar
  3. Almor, A. & Sloman, S. (1996), ‘Is deontic reasoning special?’ Psychological Review, 103, 374-380.Google Scholar
  4. Anderson, J.R. (1993), Rules of the Mind, Hillsdale, NJ: Erlbaum.Google Scholar
  5. Anderson, J.R., Greeno, J.G., Kline, P.J., & Neves, D.M. (1981), ‘Acquisition of problem solving skill’, in J.R. Anderson, ed., Cognitive Skills and Their Acquisition. Hillsdale, NJ: Erlbaum.Google Scholar
  6. Ashall, F. (1994). Remarkable Discoveries. Cambridge; Cambridge University Press.Google Scholar
  7. Ashley, K. (1990), Modeling Legal Argument: Reasoning with Cases and Hypotheticals, Cambridge, MA: MIT Press.Google Scholar
  8. Atwood, M.E., & Polson, P.G. (1976), ‘A process model for water jug problems’, Cognitive Psychology 8, 191-216.Google Scholar
  9. Bartlett, F.C. (1958), Thinking, New York: Basic Books.Google Scholar
  10. Brachman, R.J. & Levesque, J., eds., (1985), Readings in knowledge representation. San Mateo, CA: Morgan Kaufman.Google Scholar
  11. Branting, K. (1991), Integrating rules and precedents for classification and explanation, Unpublished Ph.D. dissertation, University of Texas at Austin.Google Scholar
  12. Brooks, R. (1991), Intelligence without reason. AI Memo 1293, MIT.Google Scholar
  13. Buchanan, B.G., Sutherland, G.L., & Feigenbaum, E.A. (1969), ‘Heuristic DENDRAL: A program for generating explanatory processes in organic chemistry’, in B. Meltzer and D. Michie, eds., Machine Intelligence 4. New York, NY: Elsevier.Google Scholar
  14. Carnap, R. (1950), Logical foundations of probability, Chicago, IL: University of Chicago Press.Google Scholar
  15. Carnap, R. (1952), The continuum of inductive methods, Chicago, II,: University of Chicago Press.Google Scholar
  16. Chase, W.G., & Simon, H.A. (1973), ‘Perception in chess’, Cognitive Psychology 4, 55-81.Google Scholar
  17. Chater, N., & Oaksford, M.R., (1990), ‘Autonomy, Implementation and Cognitive Architecture: A Reply to Fodor and Pylyshyn’, Cognition 34, 93-107.Google Scholar
  18. Chater, N., & Oaksford, M.R. (1993), ‘Logicism, mental models and everyday reasoning: Reply to Garnham’, Mind & Language 8, 72-89.Google Scholar
  19. Cheng, P.W., & Novick, L.R. (1992), ‘Covariation in natural causal induction’, Psychological Review 99, 365-382.Google Scholar
  20. Churchland, P.M. (1989), A Neurocomputational Perspective, Cambridge, MA: Bradford Books/MIT Press.Google Scholar
  21. Churchland, P. S. (1986), Neurophilosophy. Cambridge, MA: Bradford Books/MIT Press.Google Scholar
  22. Coulter, J. (1983), Rethinking Cognitive Theory. London: Macmillan.Google Scholar
  23. Darden, L. (1991), Theory Change in Science: Strategies from Mendelian Genetics, Oxford: Oxford University Press.Google Scholar
  24. Dayal, S., Harmer, M., Johnson, P., & Mead, D. (1993), ‘Beyond Knowledge Representation: Commercial Uses for Legal Knowledge Bases’, Proceedings of the Fourth International Conference on Artificial Intelligence and Law, Ann Arbor, MI: Association for Computing Machinery.Google Scholar
  25. Duda, R.O., Hart, P.E. & Nilsson, N.J. (1976), ‘Subjective Bayesianmethods for rule-based inference systems’, Proceedings National Computer Conference (AFIPS), vol. 15; reprinted in Shafer & Pearl (1990): 274-281.Google Scholar
  26. Evans, J.St.B.T. (1989), Bias in human reasoning: Causes and consequences, Hillsdale, NJ: Erlbaum.Google Scholar
  27. Evans, J.St.B.T., Newstead, S.E., & Byrne, R.M.J. (1993), Human Reasoning. Brighton: Erlbaum.Google Scholar
  28. Evans, J.St.B.T. & Over, D. E. (1996), Rationality in the selection task: Epistemic utility versus uncertainty reduction. Psychological Review, 103, 356-363.Google Scholar
  29. Fodor, J.A. (1975), The language of thought, New York: Thomas Crowell.Google Scholar
  30. Fodor, J.A. (1983), The modularity of mind, Cambridge, MA: MIT Press.Google Scholar
  31. Fodor, J.A. (1987), Psychosemantics: The problem of meaning in the philosophy of mind, Cambridge, MA: MIT Press.Google Scholar
  32. Fodor, J.A., & Pylyshyn, Z.W. (1988), ‘Connectionism and cognitive architecture: A critical analysis’, Cognition 28, 3-71.Google Scholar
  33. Gagn´e, R.M., & Smith, E.C. Jr. (1962), ‘A study of the effects of verbalization on problem solving’, Journal of Experimental Psychology 63, 12-18.Google Scholar
  34. Gardner, H. (1985), The mind's new science. New York: Basic Books.Google Scholar
  35. Giere, R. N. (1988). Explaining science: A cognitive approach, Chicago: University of Chicago Press.Google Scholar
  36. Gigerenzer, G., & Goldstein, D. (in press), ‘Reasoning the fast and frugal way’, Psychological Review.Google Scholar
  37. Glymour, C. (1991), ‘The hierarchies of knowledge and the mathematics of discovery’, Minds and Machines 1, 75-95.Google Scholar
  38. Gold, E.M. (1967), ‘Language identification in the limit’, Information and Control 16, 447-474.Google Scholar
  39. Gopnik, A. (1993), ‘How we know our own minds: The illusion of first-person knowledge of intentionality’, Behavioral and Brain Sciences, 16, 1-14.Google Scholar
  40. Greeno, J.G. (1974), ‘Hobbits and orcs: Acquisition of a sequential concept’, Cognitive Psychology 6, 270-292.Google Scholar
  41. Hanson, N. R. (1958), Patterns of Discovery, Cambridge: Cambridge University Press.Google Scholar
  42. Hanson, N. R. (1961), Is there a logic of discovery? In H. Feigl & G. Maxwell (Eds.), Current Issues in the Philosophy of Science, New York: Holt, Rinehart and Winston, pp. 20-35.Google Scholar
  43. Izard, C.E., & Zajonc, R.B., eds., (1984), Emotions, cognition, and behavior, Cambridge: Cambridge University Press.Google Scholar
  44. Johnson-Laird, P.N. (1983), Mental Models, Cambridge: Cambridge University Press.Google Scholar
  45. Johnson-Laird, P.N., & Byrne, R.M.J. (1991), Deduction, Hillsdale, NJ: Erlbaum.Google Scholar
  46. Kahneman, D., Slovic, P., & Tversky, A., eds., (1982), Judgement under uncertainty: Heuristics and biases, Cambridge: Cambridge University Press.Google Scholar
  47. Klayman, J. & Ha, Y. (1987), ‘Confirmation, disconfirmation and information in hypothesis testing’. Psychological Review, 94, 211-228.Google Scholar
  48. Lakoff, G. (1987), Women, fire, and dangerous things: What categories reveal about the mind. Chicago: University of Chicago Press.Google Scholar
  49. Laming, D. (1996), ‘On the analysis of irrational data selection: A critique of Oaksford & Chater (1994)’. Psychological Review, 103, 364-373.Google Scholar
  50. Langacker, R.W. (1987), Foundations of cognitive grammar. Stanford, CA: Stanford University Press.Google Scholar
  51. Langley, P., Simon, H.A., Bradshaw, G.L., & Zytkow, J.M. (1987), Scientific discovery, Cambridge, MA: MIT Press.Google Scholar
  52. Latour, B. & Woolgar, S. (1979), Laboratory life, Beverley Hills, CA: Sage.Google Scholar
  53. LeDoux, J.E. (1991), ‘Emotion and the limbic system concept.’ Concepts in Neuroscience, 2, 169- 199.Google Scholar
  54. LeDoux, J.E. (1992), ‘Brain mechanisms of emotion and emotional learning.’ Current Opinion in Neurobiology, 2, 191–197.Google Scholar
  55. Lovett, M.C. & Anderson, J.R. (1994), Effects of solving related proofs on memory and transfer in geometry problem solving. Journal of Experimental Psychology: Learning, Memory and Cognition, 20, 366-378.Google Scholar
  56. Manktelow, K.I., & Over, D.E. (1987), ‘Reasoning and rationality’, Mind and Language 2, 199-219.Google Scholar
  57. Manktelow, K.I., & Over, D.E. (1991), ‘Social roles and utilities in reasoning with deontic conditionals’</del>'</del>, Cognition 39, 85-105.Google Scholar
  58. McCarthy, J., & Hayes, P (1969), ‘Some philosophical problems from the standpoint of artificial intelligence’, in B. Meltzer and D. Michie, eds., Machine Intelligence 4, Edinburgh: Edinburgh University Press.Google Scholar
  59. Morris, W.E., & Richardson, R.C. (1995), ‘How notto demarcate cognitive science and folk psychology: A response to Pickering and Chater’, Minds and Machines 5, 339-355.Google Scholar
  60. Nersessian, N. (Ed.) (1987), The Process of Science: Contemporary Philosophical Approaches to Understanding Scientific Practice, Dordrecht: Nijhoff.Google Scholar
  61. Newell, A. & Simon, H.A. (1972), Human Problem Solving, Englewood Cliffs, NJ: Prentice Hall.Google Scholar
  62. Oaksford, M.R., & Chater, N. (1991), ‘Against Logicist Cognitive Science’, Mind and Language 6, 1-38.Google Scholar
  63. Oaksford, M.R., & Chater, N. (1993), ‘Reasoning Theories and Bounded Rationality’, in K. Manktelow & D. Over (Eds.), Rationality, London: Routeledge, pp. 31-60.Google Scholar
  64. Oaksford, M., & Chater, N. (1994), ‘Arational analysis of the selection task as optimal data selection’, Psychological Review 101, 608-631.Google Scholar
  65. Oaksford, M.R., & Chater, N. (1995a), ‘Information gain explains relevance which explains the selection task’, Cognition 57, 97-108.Google Scholar
  66. Oaksford, M., & Chater, N. (1995b), ‘Theories of reasoning and the computational explanation of everyday inference’, Thinking and Reasoning 1, 121-152.Google Scholar
  67. Oaksford, M.R. & Chater, N. (1996), ‘Rational and irrational analysis of the selection task’, Psychological Review, 103, 381-391.Google Scholar
  68. Pearl, J. (1988), Probabilistic reasoning in intelligent systems, San Mateo, CA: Morgan Kaufman.Google Scholar
  69. Perner, J. (1991), Understanding the representational mind. Cambridge, MA: MIT Press.Google Scholar
  70. Phillips, L. D. & Edwards, W. (1966), ‘Conservatism in a simple probability inference task’, Journal of Experimental Psychology, 72, 346-354.Google Scholar
  71. Pickering, M.J, & Chater, N. (1995), ‘Why cognitive science is not formalized folk psychology’, Minds and Machines 5, 309-337.Google Scholar
  72. Popper, K.R. (1959), The logic of scientific discovery. London: Hutchinson.Google Scholar
  73. Posner, M. (Ed.) (1989), Foundations of cognitive science. Cambridge, MA: MIT Press.Google Scholar
  74. Putnam, H. (1965), ‘Trial and error predicates’, Journal of Symbolic Logic 30, 49-57.Google Scholar
  75. Pylyshyn, Z.W. (1984), Computation and cognition, Cambridge, MA: MIT Press.Google Scholar
  76. Quine, W.V.O. (1953), ‘Two dogmas of empiricism’, From a logical point of view, Cambridge, MA: Harvard University Press, pp. 20-46.Google Scholar
  77. Reichenbach, H. (1938), Experience and Prediction, Chicago: Chicago University Press.Google Scholar
  78. Rips, L.J. (1994), The Psychology of Proof. Cambridge, MA: MIT Press.Google Scholar
  79. Samuel, A.G. (1959), ‘Some studies in machine learning using the game of checkers’, IBM Journal of Research and Development 2, 320-335.Google Scholar
  80. Schachter, S. & Singer, J.E. (1962), ‘Cognitive, social and physiological determinants of emotional state’. Psychological Review, 63, 379-399.Google Scholar
  81. Schachter, S. (1964), ‘The interaction of cognitive and physiological determinants of emotional state’. In Berkowitz, L. (Ed.) Advances in Experimental Social Psychology, New York: Academic Press.Google Scholar
  82. Shafer, G. & Pearl, J., eds., (1990), Readings in uncertain reasoning, San Mateo, CA: Morgan Kaufman.Google Scholar
  83. Shannon, C.E., & Weaver, W. (1949), The mathematical theory of communication, Urbana, II.: University of Illinois Press.Google Scholar
  84. Shavlik, J.W., & Dietterich, T.G., eds., (1990), Readings in machine learning, San Mateo, CA: Morgan Kaufman.Google Scholar
  85. Shortliffe, E.H. & Buchanan, B.G. (1975), ‘A model of inexact reasoning in medicine’, Mathematical Biosciences 23, 351-379.Google Scholar
  86. Simon, H.A. & Gilmartin, K.J. (1973), ‘A simulation for chess positions’. Cognitive Psychology, 5, 29-46.Google Scholar
  87. Stich, S. (1983), From folk psychology to cognitive science, Cambridge, MA: MIT Press. TWO PROJECTS FOR UNDERSTANDING THE MIND 569Google Scholar
  88. Suchman, L. (1987), Plans and situated actions: The problem of human-machine communication, Cambridge: Cambridge University Press.Google Scholar
  89. Thagard, P. (1988), Computational philosophy of science, Cambridge, MA: MIT Press.Google Scholar
  90. Thagard, P. (1992), Conceptual revolutions, Princeton: Princeton University Press.Google Scholar
  91. Tweney, R.D. (1985), Faraday's discovery of induction: A cognitive approach. In D. Gooding & F. James (Eds.) Faraday rediscovered: Essays on the life and work of Michael Faraday, 1791-1867, New York: Stockton, pp. 189-209.Google Scholar
  92. Tweney, R.D., Doherty, M.E. & Mynatt, C.R. (Eds.) (1981), On scientific thinking, New York: Columbia University Press.Google Scholar
  93. Wason, P.C. (1966), ‘Reasoning’, in Foss, B. (Ed.), New horizons in psychology, Harmondsworth, Middlesex: Penguin.Google Scholar
  94. Wason, P.C. (1968), ‘Reasoning about a rule’, Quarterly Journal of Experimental Psychology, 20, 273-281.Google Scholar
  95. Wason, P.C., & Johnson-Laird, P.N. (1972), The psychology of reasoning: Structure and content, Cambridge, MA: Harvard University Press.Google Scholar
  96. Wason, P.C., & Johnson-Laird, P.N. (Eds.) (1977), Thinking: Readings in Cognitive Science, Cambridge: Cambridge University Press.Google Scholar
  97. Wellman, H. (1990), The Child's Theory of Mind, Cambridge, MA: MIT Press.Google Scholar

Copyright information

© Kluwer Academic Publishers 1997

Authors and Affiliations

  • Nick Chater
    • 1
  • Martin Pickering
    • 2
  1. 1.Department of PsychologyUniversity of WarwickCoventryUnited Kingdom
  2. 2.Human Communication Research Centre, Department of PsychologyUniversity of GlasgowGlasgowUnited Kingdom

Personalised recommendations