Robust control theory is a tool for assessing decision rules when a decision maker distrusts either the specification of transition laws or the distribution of hidden state variables or both. Specification doubts inspire the decision maker to want a decision rule to work well for a ∅ of models...

In the present paper, we propose a robust decision methodology, when there is some ambiguity concerning the potential future scenarii about decision variables. The decision maker considers several prior models for those scenarii and displays an ambiguity aversion against them. A two step...

We connect variational preferences with the likelihood functions and prior probabilities over parameters that are building blocks of statistics and econometrics. We use relative entropy and other statistical divergences as cost functions in the variational preferences of someone who is ambiguous...

The authors adapt modern control theoretic techniques based on robust control theory to economic modelling and decision making. The main motivation behind the proposed approach is that concern about model misspecification in economics leads to decision strategies that work over the set of nearby...

General Remarks on Robust Solutions -- Modeling of Uncertainty and Probabilistic Issues -- On Joint Modelling of Random Uncertainty and Fuzzy Imprecision -- On the Approximation of a Discrete Multivariate Probability Distribution Using the New Concept of -Cherry Junction Tree -- Robust Solutions...