Dynamically consistent updating of multiple prior beliefs -- An algorithmic approach

Authors:
Eran Hanany;Peter Klibanoff;Erez Marom
Affiliations:
Department of Industrial Engineering, Tel Aviv University, Tel Aviv 69978, Israel;Department of Managerial Economics and Decision Sciences, Kellogg School of Management, Northwestern University, Evanston, IL 60208, USA;Department of Industrial Engineering, Tel Aviv University, Tel Aviv 69978, Israel
Venue:
International Journal of Approximate Reasoning
Year:
2011

Citing 5
Cited 0

Dynamic decision making with belief functions

Advances in the Dempster-Shafer theory of evidence
A new approach to updating beliefs

UAI '90 Proceedings of the Sixth Annual Conference on Uncertainty in Artificial Intelligence
Uncertainty Aversion with Second-Order Utilities and Probabilities

Management Science
Updating under unknown unknowns: An extension of Bayes' rule

International Journal of Approximate Reasoning
Change rules for hierarchical beliefs

International Journal of Approximate Reasoning

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper develops algorithms for dynamically consistent updating of ambiguous beliefs in the maxmin expected utility model of decision making under ambiguity. Dynamic consistency is the requirement that ex-ante contingent choices are respected by updated preferences. Such updating, in this context, implies dependence on the feasible set of payoff vectors available in the problem and/or on an ex-ante optimal act for the problem. Despite this complication, the algorithms are formulated concisely and are easy to implement, thus making dynamically consistent updating operational in the presence of ambiguity.