Taxonomy, Structure, and Implementation of Evidential Reasoning

TL;DR

This paper explores the fundamental elements and structures of evidential reasoning problems, proposing a formal framework using Bayesian networks and state space models, and illustrating a decision-making cycle for military assessments.

Contribution

It introduces a structured approach to evidential reasoning problems and a decision-making cycle, laying groundwork for expert system development in situation assessment.

Findings

Framework using Bayesian inference networks and state space formalism

A human-oriented decision cycle for evidential reasoning

Potential basis for an expert system shell for situation assessment

Abstract

The fundamental elements of evidential reasoning problems are described, followed by a discussion of the structure of various types of problems. Bayesian inference networks and state space formalism are used as the tool for problem representation. A human-oriented decision making cycle for solving evidential reasoning problems is described and illustrated for a military situation assessment problem. The implementation of this cycle may serve as the basis for an expert system shell for evidential reasoning; i.e. a situation assessment processor.