Incidence Calculus: A Mechanism for Probabilistic Reasoning

TL;DR

Incidence Calculus is a new probabilistic reasoning mechanism that uses set-based representations of uncertainty to enable truth-functional connectives, addressing limitations of purely numeric approaches.

Contribution

It introduces Incidence Calculus, a novel set-based probabilistic logic mechanism that supports truth-functional connectives, enhancing automation of uncertainty in expert systems.

Findings

Provides a probabilistic logic with truth-functional connectives

Uses sets of points to represent uncertainty

Addresses limitations of numeric probabilistic mechanisms

Abstract

Mechanisms for the automation of uncertainty are required for expert systems. Sometimes these mechanisms need to obey the properties of probabilistic reasoning. A purely numeric mechanism, like those proposed so far, cannot provide a probabilistic logic with truth functional connectives. We propose an alternative mechanism, Incidence Calculus, which is based on a representation of uncertainty using sets of points, which might represent situations, models or possible worlds. Incidence Calculus does provide a probabilistic logic with truth functional connectives.