Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
397931 | International Journal of Approximate Reasoning | 2011 | 17 Pages |
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.
► We consider the maxmin expected utility model of decision making under ambiguity. ► We focus on dynamically consistent updating for all instances of this model and all non-null events. ► We develop algorithms to implement such dynamically consistent update rules.