Conditional Plausibility Measures and Bayesian Networks

TL;DR

This paper introduces a unified framework for various uncertainty measures using algebraic conditional plausibility measures and demonstrates how Bayesian networks can be applied within this framework.

Contribution

It generalizes the concept of conditional plausibility measures and extends Bayesian network techniques to a broader class of uncertainty representations.

Findings

Unified algebraic framework for different uncertainty measures

Bayesian networks applicable to algebraic conditional plausibility measures

Potential for broader applications in uncertain reasoning

Abstract

A general notion of algebraic conditional plausibility measures is defined. Probability measures, ranking functions, possibility measures, and (under the appropriate definitions) sets of probability measures can all be viewed as defining algebraic conditional plausibility measures. It is shown that the technology of Bayesian networks can be applied to algebraic conditional plausibility measures.