Synthese 172 (1) (2010)
|Abstract||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.|
|Keywords||No keywords specified (fix it)|
|Through your library||Configure|
Similar books and articles
Festa, Roberto, Optimum Inductive Methods. A Study in Inductive Probability, Bayesian Statistics, and Verisimilitude.
Frederick Eberhardt & David Danks (2011). Confirmation in the Cognitive Sciences: The Problematic Case of Bayesian Models. Minds and Machines 21 (3):389-410.
M. Wayne Cooper (1992). Should Physicians Be Bayesian Agents? Theoretical Medicine and Bioethics 13 (4).
Kenny Easwaran (2011). Bayesianism I: Introduction and Arguments in Favor. Philosophy Compass 6 (5):312-320.
Mark Sargent (2009). Answering the Bayesian Challenge. Erkenntnis 70 (2):237 - 252.
Stephan Hartmann & Jan Sprenger (forthcoming). Bayesian Epistemology. In Duncan Pritchard & Sven Bernecker (eds.), Routledge Companion to Epistemology. Routledge.
Samir Okasha (2003). Probabilistic Induction and Hume's Problem: Reply to Lange. Philosophical Quarterly 53 (212):419–424.
Added to index2009-02-23
Total downloads90 ( #7,748 of 549,078 )
Recent downloads (6 months)1 ( #63,317 of 549,078 )
How can I increase my downloads?