Intelligent Diagnosis Systems
Karthik Balakrishnan, Vasant Honavar · Journal of Intelligent Systems · 1998
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.