Dynamically consistent updating of multiple prior beliefs - An algorithmic approach

Eran Hanany, Peter Klibanoff, Erez Marom

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)1198-1214
Number of pages17
JournalInternational Journal of Approximate Reasoning
Volume52
Issue number8
DOIs
StatePublished - Nov 2011

Keywords

  • Ambiguity
  • Risk analysis
  • Uncertainty modeling
  • Updating beliefs
  • Utility theory

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