This paper extends decision theory under imprecise probabilistic information to dynamic settings. We explore the relationship between the given objective probabilistic information, an agent's subjective multiple priors, and updating. Dynamic consistency implies rectangular sets of priors at the...

This paper extends decision theory under imprecise probabilistic information to dynamic settings. We explore the relationship between the given objective probabilistic information, an agent's subjective multiple priors, and updating. Dynamic consistency implies rectangular sets of priors at the...

This paper presents an axiomatic model of decision making which incorporates objective but imprecise information. We axiomatize a decision criterion of the multiple priors (or maxmin expected utility) type. The model achieves two primary objectives. First, it explains how subjective belief...

This paper presents an axiomatic model of decision making which incorporates objective but imprecise information. We axiomatize a decision criterion of the multiple priors (or maxmin expected utility) type. The model achieves two primary objectives. First, it explains how subjective belief...

This paper presents an axiomatic model of decision making under uncertainty which incorporates objective but imprecise information. Information is assumed to take the form of a probability-possibility set, that is, a set $P$ of probability measures on the state space. The decision maker is told...