Plausibility Measures: A User's Guide

Understand

We examine a new approach to modeling uncertainty based on plausibility measures, where a plausibility measure just associates with an event its plausibility, an element is some partially ordered set.

• This approach is easily seen to generalize other approaches to modeling uncertainty, such as probability measures, belief functions, and possibility measures.
• The lack of structure in a plausibility measure makes it easy for us to add structure on an "as needed" basis, letting us examine what is required to ensure that a plausibility measure has certain properties of interest.
• This gives us insight into the essential features of the properties in question, while allowing us to prove general results that apply to many approaches to reasoning about uncertainty.