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...

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...

We provide a general theorem on the aggregation of preferences under uncertainty. We study, in the Anscombe-Aumann setting a wide class of preferences, that includes most known models of decision under uncertainty (and state-dependent versions of these models). We prove that aggregation is...

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...

We provide a model of decision making under uncertainty in which the decision maker reacts to imprecision of the available data. Data is represented by a set of probability distributions. We axiomatize a decision criterion of the maxmin expected utility type, in which the revealed set of priors...

We provide a general theorem on the aggregation of preferences under uncertainty. We study, in the Anscombe-Aumann setting a wide class of preferences that includes most known models of decision under uncertainty (and state-dependent versions of these models). We prove that aggregation is...

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 studies the costs and benefits of delegating decisions to superiorly informed agents relative to the use of rigid, non discretionary contracts. The main focus of the paper lies in the analysis of the costs of delegation, primarily agency costs, versus their benefits, primarily 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...