An Improper Introduction to Epistemic Utility Theory

Conference paper
Part of the The European Philosophy of Science Association Proceedings book series (EPSP, volume 1)

Abstract

In epistemic utility theory, we apply the tools of decision theory to justify epistemic norms. We treat the possible epistemic states of an agent as if they were epistemic actions between which she must choose. And we ask how we should measure the purely epistemic utility of being in such a state. We then apply the general apparatus of decision theory to determine which epistemic states are rational in a given situation from a purely epistemic point of view; and how our epistemic states should evolve over time. In this paper, I survey recent attempts to justify the tenets of Bayesian epistemology by appealing to epistemic utility theory. And I raise objections to arguments based on the technical notion of propriety.

Keywords

Epistemic State Credence Function Epistemic Norm Dutch Book Maximize Expect Utility 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Bostrom, Nick. 2002. Anthropic bias: Observation selection effects in science and philosophy. New York: Routledge.Google Scholar
  2. De Finetti, Bruno. 1931. Sul significato soggettivo della probabilita. Fundamenta Mathematicae 17: 298–329.Google Scholar
  3. Elga, Adam. 2000. Self-locating belief and the sleeping beauty problem. Analysis 60(2): 143–147.CrossRefGoogle Scholar
  4. Gibbard, Allan. 2008. Rational credence and the value of truth. In Oxford studies in epistemology volume 2, eds. T. Gendler and J. Hawthorne, 143–164. Oxford: Oxford University Press.Google Scholar
  5. Greaves, Hilary, and David Wallace. 2006. Justifying conditionalization: Conditionalization maximizes expected epistemic utility. Mind 115(459): 607–632.CrossRefGoogle Scholar
  6. Hájek, Alan. 2008. Arguments for—or against—probabilism? The British Journal for the Philosophy of Science 59(4): 793–819.CrossRefGoogle Scholar
  7. Jeffrey, Richard. 1965. Logic of decision. New York: McGraw-Hill.Google Scholar
  8. Joyce, James M. 1998. A nonpragmatic vindication of probabilism. Philosophy of Science 65(4): 575–603.CrossRefGoogle Scholar
  9. Joyce, James M. 2009. Accuracy and coherence: Prospects for an alethic epistemology of partial belief. In Degrees of belief, eds. F. Huber and C.~Schmidt-Petri, 263–297. New York: Springer.CrossRefGoogle Scholar
  10. Leitgeb, Hannes, and Richard Pettigrew. 2010a. An objective justification of Bayesianism I: Measuring inaccuracy. Philosophy of Science 77: 201–235.CrossRefGoogle Scholar
  11. Leitgeb, Hannes, and Richard Pettigrew. 2010b. An objective justification of Bayesianism II: The consequences of minimizing inaccuracy. Philosophy of Science 77: 236–272.CrossRefGoogle Scholar
  12. Lewis, David. ed. 1999. Why conditionalize? In Papers in metaphysics and epistemology, 403–407. Cambridge, UK: Cambridge University Press.Google Scholar
  13. Maher, Patrick. 1993. Betting on theories. In Cambridge studies in probability, induction, and decision theory. Cambridge, UK: Cambridge University Press.Google Scholar
  14. Maher, Patrick. 2002. Joyce’s argument for probabilism. Philosophy of Science 69(1): 73–81.CrossRefGoogle Scholar
  15. Oddie, Graham. 1997. Conditionalization, cogency, and cognitive value. British Journal for the Philosophy of Science 48: 533–541.CrossRefGoogle Scholar
  16. Predd, Joel, Robert Seiringer, Elliott H. Lieb, Daniel Osherson, Vincent Poor, and Sanjeev Kulkarni. 2009. Probabilistic coherence and proper scoring rules. IEEE Transactions on Information Theory 55(10): 4786–4479.CrossRefGoogle Scholar
  17. Ramsey, Frank P. 1931. Truth and probability. In The foundations of mathematics and other logical essays, ed. R.B. Braithwaite 156–198. London: Routledge and Kegan Paul.Google Scholar
  18. Savage, Leonard J. 1954. The foundations of statistics. New York: Wiley.Google Scholar
  19. Shimony, Abner. 1955. Coherence and the axioms of confirmation. Journal of Symbolic Logic 20: 1–28.CrossRefGoogle Scholar
  20. Skyrms, Brian. 1987. Dynamic coherence and probability kinematics. Philosophy of Science 54(1): 1–20.CrossRefGoogle Scholar
  21. Van Fraassen, Bas C. 1981. A problem for relative information minimizers. British Journal for the Philosophy of Science 32(4): 375–379.CrossRefGoogle Scholar
  22. Van Fraassen, Bas C. 1984. Belief and the will. Journal of Philosophy 81: 235–256.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  1. 1.Department of PhilosophyUniversity of BristolBristolUK

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