- 308 Downloads
Bayesian decision theory is here construed as explicating a particular concept of rational choice and Bayesian probability is taken to be the concept of probability used in that theory. Bayesian probability is usually identified with the agent’s degrees of belief but that interpretation makes Bayesian decision theory a poor explication of the relevant concept of rational choice. A satisfactory conception of Bayesian decision theory is obtained by taking Bayesian probability to be an explicatum for inductive probability given the agent’s evidence.
KeywordsBayesian probability Logical probability Inductive probability Subjective probability Degrees of belief Decision theory Expected utility Explication Carnap
- Carnap, R. (1950). Logical foundations of probability (2nd ed., 1962). Chicago: University of Chicago Press.Google Scholar
- Carnap R. (1952) The continuum of inductive methods. University of Chicago Press, ChicagoGoogle Scholar
- Carnap R. (1963) Replies and systematic expositions. In: Schilpp P.A. (eds) The philosophy of Rudolf Carnap. Open Court, La Salle, IL, pp 859–1013Google Scholar
- Kahneman, D., Slovic, P., Tversky, A. (eds) (1982) Judgment under uncertainty: Heuristics and biases. Cambridge University Press, New YorkGoogle Scholar
- Maher, P. (2008). Physical probability. In C. Glymour, W. Wang, & D. Westerståhl (Eds.), Logic, methodology and philosophy of science: Proceedings of the thirteenth international congress. London: Kings College Publications (To appear).Google Scholar