Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
403246 | Knowledge-Based Systems | 2006 | 9 Pages |
Abstract
Debugging an expert system is virtually unfeasible without explanation facilities, especially in the case of probabilistic expert systems, whose way of reasoning is completely different from that of human experts. Unfortunately, almost currently available tools for building probabilistic graphical models offer no explanation facility. This paper shows how the explanation capabilities provided by Elvira, a software tool for editing and evaluating probabilistic graphical models, have helped us in the debugging of two medical Bayesian networks: Prostanet, for the diagnosis of prostate cancer, and hepar ii, for liver disorders.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Carmen Lacave, Agnieszka Oniśko, Francisco J. Díez,