A Belief-Function Based Decision Support System

TL;DR

This paper introduces a decision support system that combines belief functions and Bayesian decision analysis, allowing users to input intuitive judgments and receive guidance on testing strategies through an integrated, user-friendly interface.

Contribution

It presents a novel integration of belief function propagation with Bayesian decision analysis using the pignistic transformation, enhancing decision support capabilities.

Findings

Effective belief propagation and decision suggestion

User-friendly interface for intuitive input

Integrated evidential and Bayesian reasoning

Abstract

In this paper, we present a decision support system based on belief functions and the pignistic transformation. The system is an integration of an evidential system for belief function propagation and a valuation-based system for Bayesian decision analysis. The two subsystems are connected through the pignistic transformation. The system takes as inputs the user's "gut feelings" about a situation and suggests what, if any, are to be tested and in what order, and it does so with a user friendly interface.