David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
This paper offers a comparison between two decision rules for use when uncertainty is depicted by a non-trivial, convex2 set of probability functions Γ. This setting for uncertainty is different from the canonical Bayesian decision theory of expected utility, which uses a singleton set, just one probability function to represent a decision maker’s uncertainty. Justifications for using a non-trivial set of probabilities to depict uncertainty date back at least a half century (Good, 1952) and a foreshadowing of that idea can be found even in Keynes’ (1921), where he allows that not all hypotheses may be comparable by qualitative probability – in accord with, e.g., the situation where the respective intervals of probabilities for two events merely overlap with no further (joint) constraints, so that neither of the two events is more, or less, or equally probable compared with the other
|Keywords||No keywords specified (fix it)|
|Categories||categorize this paper)|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library||
References found in this work BETA
No references found.
Citations of this work BETA
No citations found.
Similar books and articles
Jonas Clausen Mork (2013). Uncertainty, Credal Sets and Second Order Probability. Synthese 190 (3):353-378.
Teddy Seidenfeld, Mark J. Schervish & Joseph B. Kadane (2010). Coherent Choice Functions Under Uncertainty. Synthese 172 (1):157 - 176.
Giuseppe Fontana & Bill Gerrard (1999). Disequilibrium States and Adjustment Processes: Towards a Historical-Time Analysis of Behaviour Under Uncertainty. Philosophical Psychology 12 (3):311 – 324.
Clare Chua Chow & Rakesh K. Sarin (2002). Known, Unknown, and Unknowable Uncertainties. Theory and Decision 52 (2):127-138.
Henry E. Kyburg (1992). Getting Fancy with Probability. Synthese 90 (2):189-203.
Henry E. Kyburg Jr (1992). Getting Fancy with Probability. Synthese 90 (2):189 - 203.
Matthew C. Wilson (2009). Creativity, Probability and Uncertainty. Journal of Economic Methodology 16 (1):45-56.
Phan H. Giang & Prakash P. Shenoy (2000). A Qualitative Linear Utility Theory for Spohn's Theory of Epistemic Beliefs. In C. Boutilier & M. Goldszmidt (eds.), Uncertainty in Artificial Intelligence 16. Morgan Kaufmann.
George Wu (1999). Anxiety and Decision Making with Delayed Resolution of Uncertainty. Theory and Decision 46 (2):159-199.
Added to index2009-01-28
Total downloads10 ( #161,288 of 1,413,339 )
Recent downloads (6 months)2 ( #94,237 of 1,413,339 )
How can I increase my downloads?