# A behavioral interpretation of belief functions

## TL;DR

This paper offers a behavioral interpretation of Shafer's belief functions, connecting them to betting scenarios and classical probability concepts, thus clarifying their practical meaning.

## Contribution

It introduces a novel behavioral interpretation of belief functions and re-derives them through a betting framework, bridging a gap in their conceptual understanding.

## Key findings

- Belief functions can be interpreted through betting scenarios.
- The interpretation aligns belief functions with classical probability principles.
- Provides a new foundation for understanding belief functions in decision-making.

## Abstract

Shafer's belief functions were introduced in the seventies of the previous century as a mathematical tool in order to model epistemic probability. One of the reasons that they were not picked up by mainstream probability was the lack of a behavioral interpretation. In this paper we provide such a behavioral interpretation, and re-derive Shafer's belief functions via a betting interpretation reminiscent of the classical Dutch Book Theorem for probability distributions. We relate our betting interpretation of belief functions to the existing literature.