BaRT: A Bayesian Reasoning Tool for Knowledge Based Systems

TL;DR

BaRT is a Bayesian reasoning tool designed for knowledge engineers to build probabilistic classifiers, effectively managing uncertainty in complex decision-making tasks like image classification and intelligence analysis.

Contribution

Introduces BART, a novel Bayesian reasoning tool that integrates probabilistic methods into knowledge-based systems for improved classificatory problem solving.

Findings

Successfully used for classifying ship images

Applied to manage uncertainty in intelligence report analysis

Demonstrates natural fit of probabilistic methods in knowledge systems

Abstract

As the technology for building knowledge based systems has matured, important lessons have been learned about the relationship between the architecture of a system and the nature of the problems it is intended to solve. We are implementing a knowledge engineering tool called BART that is designed with these lessons in mind. BART is a Bayesian reasoning tool that makes belief networks and other probabilistic techniques available to knowledge engineers building classificatory problem solvers. BART has already been used to develop a decision aid for classifying ship images, and it is currently being used to manage uncertainty in systems concerned with analyzing intelligence reports. This paper discusses how state-of-the-art probabilistic methods fit naturally into a knowledge based approach to classificatory problem solving, and describes the current capabilities of BART.