Decision theory and cognitive choice

Original Paper in Decision and Game Theory

Abstract

The focus of this study is cognitive choice: the selection of one cognitive option (a hypothesis, a theory, or an axiom, for instance) rather than another. The study proposes that cognitive choice should be based on the plausibilities of states posited by rival cognitive options and the utilities of these options' information outcomes. The proposal introduces a form of decision theory that is novel because comparative; it permits many choices among cognitive options to be based on merely comparative plausibilities and utilities. This form of decision theory intersects with recommendations by advocates of decision theory for cognitive choice, on the one hand, and defenders of comparative evaluation of scientific hypotheses and theories, on the other. But it differs from prior decision-theoretic proposals because it requires no more than minimal precision in specifying plausibilities and utilities. And it differs from comparative proposals because none has shown how comparative evaluations can be carried out within a decision-theoretic framework.

Keywords

Decision theory Cognitive choice Probability Plausibility Utility Information 

Notes

Acknowledgements

Prasanta Bandyopadhyay, James Franklin, Theo Kuipers, and Ana Portilla contributed insightful comments on an earlier version of this paper. Two anonymous referees and the editors of European Journal for Philosophy of Science offered highly constructive criticism of the present version. Audiences at the University of Groningen in the Netherlands, Complutense University and the University of Alcalá de Henares in Spain, and Visva Bharati University in India also provided valuable feedback. I am grateful to them all.

References

  1. Aumann, R. J. (1962). Utility theory without the completeness axiom. Econometrica, 30, 445–462.CrossRefGoogle Scholar
  2. Baumann, P. (2005). Theory choice and the intransitivity of ‘is a better theory than’. Philosophy of Science, 72, 231–240.CrossRefGoogle Scholar
  3. Behn, R. D., & Vaupel, J. W. (1982). Quick analysis for busy decision makers. New York: Basic Books.Google Scholar
  4. Black, M. (1985). Making intelligent choices: how useful is decision theory? Dialectica, 39, 19–34.CrossRefGoogle Scholar
  5. Bryson, B. (2003). A short history of nearly everything. New York: Broadway Books.Google Scholar
  6. Chu, F. C., & Halpern, J. Y. (2004). Great expectations. Part II: generalized expected utility as a universal decision rule. Artificial Intelligence, 159, 207–229.CrossRefGoogle Scholar
  7. Chu, F. C., & Halpern, J. Y. (2008). Great expectations. Part I: on the customizability of generalized expected utility. Theory and Decision, 64, 1–36.CrossRefGoogle Scholar
  8. de Finetti, B. (1937). La prévision, ses lois logiques, ses sources subjectives. Annales de l’Institut Henri Poincaré, 7, 1–68. Trans. Foresight: Its Logical Laws, Its Subjective Sources. In Henry E. Kyburg and Howard E. Smokler (Eds.), Studies in Subjective Probability (pp. 53–118). New York: Krieger, 1980.Google Scholar
  9. Dewey, J., & Tufts, J. H. (1932). Ethics, rev. ed. New York: Holt.Google Scholar
  10. Elster, J. (1979). Ulysses and the Sirens: Studies in rationality and irrationality. Cambridge: Cambridge University Press.Google Scholar
  11. Elster, J. (2000). Ulysses unbound: Studies in rationality, precommitment, and constraints. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  12. Festa, R. (1999). Scientific values, probability, and acceptance. In R. Rossini Favretti, G. Sandri, & R. Scazzieri (Eds.), Incommensurability and translation: Kuhnian perpectives on scientific communication and theory change (pp. 323–338). Cheltenham: Elgar.Google Scholar
  13. Fishburn, P. C. (1986). The axioms of subjective probability. Statistical Science, 1, 335–358.CrossRefGoogle Scholar
  14. Fishburn, P. C. (1991). Non-transitive preferences in decision theory. Journal of Risk and Uncertainty, 4, 113–134.CrossRefGoogle Scholar
  15. Floridi, L. (2004). Outline of a theory of strongly semantic information. Minds and Machines, 14, 197–221.CrossRefGoogle Scholar
  16. Franklin, J. (2001). The science of conjecture: Evidence and probability before Pascal. Baltimore and London: The Johns Hopkins University Press.Google Scholar
  17. Friedman, N., & Halpern, J. Y. (1995). Plausibility measures: A user’s guide. In P. Besnard & S. Hanks (Eds.), Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence (UAI ‘95) (pp. 175–184). San Mateo: Kaufmann.Google Scholar
  18. Gärdenfors, P., & Sahlin, N.-E. (1982). Unreliable probabilities, risk taking, and decision making. Synthese, 53, 361–386.CrossRefGoogle Scholar
  19. Giere, R. N. (1985). Constructive realism. In P. M. Churchland & C. A. Hooker (Eds.), Images of science (pp. 75–98). Chicago: University of Chicago Press.Google Scholar
  20. Good, I. J. (1962). Subjective probability as the measure of a non-measurable set. In P. Suppes, E. Nagel, & A. Tarski (Eds.), Logic, methodology, and the philosophy of science (pp. 319–329). Stanford: Stanford University Press.Google Scholar
  21. Gowans, C. W. (1987). Moral dilemmas. New York: Oxford University Press.Google Scholar
  22. Greenspan, P. (1983). Moral dilemmas and guilt. Philosophical Studies, 43, 117–125.CrossRefGoogle Scholar
  23. Halpern, J. Y. (2003). Reasoning about uncertainty. Cambridge: The MIT Press.Google Scholar
  24. Hempel, C. G. (1960). Inductive inconsistencies. Synthese, 12, 439–469. Rpt. in Aspects of Scientific Explanation, Carl G. Hempel (pp. 53–79). New York: The Free Press and London: Collier Macmillan, 1965.Google Scholar
  25. Hintikka, J. (1970a). On semantic information. In J. Hintikka & P. Suppes (Eds.), Information and inference (pp. 3–27). Dordrecht: Reidel.Google Scholar
  26. Hintikka, J. (1970b). Surface information and depth information. In J. Hintikka & P. Suppes (Eds.), Information and inference (pp. 263–297). Dordrecht: Reidel.Google Scholar
  27. Hintikka, J. (1983). The game of language: Studies in game-theoretical semantics and its applications. Dordrecht: Reidel.Google Scholar
  28. Hintikka, J., & Pietarinen, J. (1966). Semantic information and inductive logic. In J. Hintikka & P. Suppes (Eds.), Aspects of inductive logic (pp. 96–112). Amsterdam: North-Holland.CrossRefGoogle Scholar
  29. Hughes, R. I. G. (1980). Rationality and intransitive preferences. Analysis, 40, 132–134.CrossRefGoogle Scholar
  30. Irvine, W. B. (2006). On desire: Why we want what we want. Oxford: Oxford University Press.Google Scholar
  31. James, W. (1897). The will to believe, and other essays in popular philosophy. New York: Longmans, Green & Co. Rpt. Cambridge, MA and London: Harvard University Press, 1979.Google Scholar
  32. Jeffrey, R. C. (1983). The logic of decision (2nd ed.). Chicago: University of Chicago Press.Google Scholar
  33. Jeffreys, H. (1931). Scientific inference. Cambridge: Cambridge University Press.Google Scholar
  34. Jeffreys, H. (1961). Theory of probability (3rd ed.). Oxford: Clarendon.Google Scholar
  35. Jensen, N. E. (1967). An introduction to Bernoullian utility theory: I. Utility functions. Swedish Journal of Economics, 69, 163–183.CrossRefGoogle Scholar
  36. Kaplan, M. (1981). A Bayesian theory of rational acceptance. The Journal of Philosophy, 78, 305–330.CrossRefGoogle Scholar
  37. Kaplan, M. (1996). Decision theory as philosophy. Cambridge: Cambridge University Press.Google Scholar
  38. Keynes, J. M. (1921). A treatise on probability. London: Macmillan. Rpt. Mineola: Dover, 2004.Google Scholar
  39. Klir, G. J. (2006). Uncertainty and information: Foundations of generalized information theory. Hoboken: Wiley.Google Scholar
  40. Kuhn, T. S. (1970). The structure of scientific revolutions (2nd ed.). Chicago: University of Chicago Press.Google Scholar
  41. Kyburg, H. E., Jr. (1961). Probability and the logic of rational belief. Middletown: Wesleyan University Press.Google Scholar
  42. Kyburg, H. E., Jr. (1979). Tyche and athena. Synthese, 40, 415–438.CrossRefGoogle Scholar
  43. Laudan, L. (1984). Science and values: The aims of science and their role in scientific debate. Berkeley: University of California Press.Google Scholar
  44. Levi, I. (1967). Gambling with truth: An essay on induction and the aims of science. New York: Knopf.Google Scholar
  45. Levi, I. (1974). On indeterminate probabilities. The Journal of Philosophy, 71, 391–418.CrossRefGoogle Scholar
  46. Levi, I. (1984). Information and inference. Decisions and revisions, Isaac Levi (pp. 51–69). Cambridge: Cambridge University Press.Google Scholar
  47. Levi, I. (1986). Hard choices: Decision making under unresolved conflict. Cambridge: Cambridge University Press.Google Scholar
  48. Lockhart, T. (2000). Moral uncertainty and its consequences. New York: Oxford University Press.Google Scholar
  49. Maher, P. (1993). Betting on theories. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  50. Morton, A., & Karjalainen, A. (2003). Contrastive knowledge. Philosophical Explorations, 6, 74–89.CrossRefGoogle Scholar
  51. Ok, E. A. (2002). Utility representation of an incomplete preference relation. Journal of Economic Theory, 104, 429–449.CrossRefGoogle Scholar
  52. Ok, E. A., Dubra, J., & Maccheroni, F. (2004). Expected utility theory without the completeness axiom. Journal of Economic Theory, 115, 118–133.CrossRefGoogle Scholar
  53. Peterson, M. (2009). An introduction to decision theory. Cambridge: Cambridge University Press.Google Scholar
  54. Pigozzi, G. (2009). Interview with John Woods. The Reasoner, 3(3), 1–4.Google Scholar
  55. Pollock, J. L. (2006). Thinking about acting: Logical foundations for rational decision making. Oxford: Oxford University Press.Google Scholar
  56. Salmon, W. (1990). The appraisal of theories: Kuhn meets Bayes. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association, 2, 325–332.Google Scholar
  57. Samuelson, P. A. (1952). Probability, utility, and the independence axiom. Econometrica, 20, 670–678.CrossRefGoogle Scholar
  58. Savage, L. J. (1972). The foundations of statistics (2nd rev. ed.) New York: Dover.Google Scholar
  59. Schaffer, J. (2004). From contextualism to contrastivism. Philosophical Studies, 11, 73–103.CrossRefGoogle Scholar
  60. Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27, 379–423. Rpt. in The Mathematical Theory of Communication, Claude E. Shannon and Warren Weaver. Urbana: University of Illinois Press, 1949.Google Scholar
  61. Simon, H. (1982). Models of bounded rationality. Cambridge: The MIT Press.Google Scholar
  62. Slote, M. (1989). Beyond optimizing: A study of rational choice. Cambridge: Harvard University Press.Google Scholar
  63. Sober, E. (1999). Testability. Proceedings and Addresses of the American Philosophical Association 73(2), 47–76.Google Scholar
  64. von Neumann, J., & Morgenstern, O. (1953). Theory of games and economic behavior (3rd ed.). Princeton: Princeton University Press.Google Scholar
  65. Weirich, P. (2004). Realistic decision theory: Rules for nonideal agents in nonideal circumstances. Oxford: Oxford University Press.Google Scholar
  66. Zimmerman, M. J. (1996). The concept of moral obligation. Cambridge: Cambridge University Press.CrossRefGoogle Scholar

Copyright information

© Springer Science + Business Media B.V. 2010

Authors and Affiliations

  1. 1.Department of PhilosophySaint Louis University—Madrid CampusMadridSpain

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