Dynamically consistent updating of multiple prior beliefs - An algorithmic approach

Eran Hanany*, Peter Klibanoff, Erez Marom

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


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


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

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Artificial Intelligence
  • Applied Mathematics


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