Partially observable Markov decision processes with imprecise parameters
Artificial Intelligence
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The specification of appropriate procedures for making inferences in the context of uncertain, incomplete or imprecise information is a key research issue in a variety of disciplines. Within and among these disciplines, great debates have occurred about the meaning and appropriateness of various proposals for reasoning under uncertainty. At the core of many of these debates are disagreements as to the appropriate meaning of the term “uncertainty”, the related term “probability”, and what it means to be unsure of one's own uncertainties. This latter issue, uncertainty about one's uncertainty, is commonly referred to as higher order uncertainty. This paper provides a brief overview of various perspectives in higher order uncertainty