BaRT: A Bayesian Reasoning Tool for Knowledge Based 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.
Cite
@article{arxiv.1304.1496,
title = {BaRT: A Bayesian Reasoning Tool for Knowledge Based Systems},
author = {Lashon B. Booker and Naveen Hota and Connie Loggia Ramsey},
journal= {arXiv preprint arXiv:1304.1496},
year = {2013}
}
Comments
Appears in Proceedings of the Fifth Conference on Uncertainty in Artificial Intelligence (UAI1989)