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.

Original languageEnglish (US)
Pages (from-to)239-290
Number of pages52
JournalJournal of Intelligent Systems
Issue number3-4
StatePublished - 1998

All Science Journal Classification (ASJC) codes

  • Software
  • Information Systems
  • Artificial Intelligence


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