ABSTRACT In most decision problems consequences of the various alternative actions depend on states determined by a generative mechanism representing some physical or social phenomenon. Model uncertainty arises because decision makers may not know this mechanism. Two types of uncertainty result, aleatory uncertainty within models and model uncertainty across them.

This talk addresses the recent developments of the field with a special focus on the need for robustness and discusses some implications for Multi Criteria Decision Analysis.