In a Markov decision problem with hidden state variables, a posterior distribution serves as a state variable and Bayes' law under an approximating model gives its law of motion. A decision maker expresses fear that his model is misspecified by surrounding it with a set of alternatives that are...

A decision maker suspects that parameters of a set of structured parametric probability models vary over time in unknown ways that he does not describe probabilistically. He expresses a fear that all of these parametric models are misspeci ed by also wanting to consider alternative unstructured...

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...