Publication Date

1996

Technical Report Number

TR95-22a

Subjects

Computing Methodologies

Abstract

This paper examines and compares several different approaches to the design of intelligent systems for diagnosis applications. These include expert systems (or knowledge-based systems), truth (or reason) maintenance systems, case-based reasoning systems, and inductive approaches like decision trees, artificial neural networks (or connectionist systems), and statistical pattern classification systems. Each of these approaches is demonstrated through the design of a system for a simple automobile fault diagnosis task. The paper also discusses the domain characteristics and design and performance requirements that influence the choice of a specific technique (or a combination of techniques) for a given application.

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