# Toward a Dempster-Shafer theory of concepts

## TL;DR

This paper extends Dempster-Shafer theory to formal concepts, enabling belief representation and combination in conceptual frameworks, which enhances reasoning under uncertainty in AI.

## Contribution

It generalizes Dempster-Shafer theory from predicates to formal concepts, introducing belief functions and combination rules for conceptual reasoning.

## Key findings

- Representation of conceptual belief functions as inner measures
- Dempster-Shafer rule of combination for formal concepts
- Enhanced reasoning under uncertainty in conceptual domains

## Abstract

In this paper, we generalize the basic notions and results of Dempster-Shafer theory from predicates to formal concepts. Results include the representation of conceptual belief functions as inner measures of suitable probability functions, and a Dempster-Shafer rule of combination on belief functions on formal concepts.