The **theory of belief functions**, also referred to as **evidence theory** or **Dempster–Shafer theory** (**DST**), is a general framework for reasoning with uncertainty, with understood connections to other frameworks such as probability, possibility and imprecise probability theories. First introduced by Arthur P. Dempster in the context of statistical inference, the theory was later developed by Glenn Shafer into a general framework for modeling epistemic uncertainty—a mathematical theory of evidence. The theory allows one to combine evidence from different sources and arrive at a degree of belief (represented by a mathematical object called belief function) that takes into account all the available evidence.

# Topic

# Evidence Theory

This topic includes the following resources and journeys:

Filters

### Type

### Experience

### Scope

3 items

## Smart Projectile State Estimation Using Evidence Theory

Intermediate

Peer Reviewed Paper

Theory

This journal article provides a very good practical understanding of Dempster-Shafer theory using sensor fusion and state estimation as the backdrop.

See More## Overview of Dempster-Shafer Theory (Evidence Theory)

Beginner

Article / Blog

Theory

This is an overview of Dempster-Shafer Theory (Evidence Theory) that provides an introduction, definition, basic information about combination rules, some issues with the theory, and the...

See More## Automatic Updates of Transition Potential Matrices in Dempster-Shafer Networ...

Advanced

Peer Reviewed Paper

Theory

Journal article that develops an evidential reasoning network capable of learning/updating the relationships between Frames of Discernment (the sets over which Dempster-Shafer reasons that...

See More