MDS: An Integrated Architecture for Associational and Model-Based Diagnosis

  • Authors:

  • Xudong W. Yu;Gautam Biswas;Jerry Weinberg

  • Affiliations:

  • Department of CS, SIUE, Edwardsville, IL 62026, USA. xyu@siue.edu;Department of EECS, Vanderbilt University, Nashville, TN 37235, USA. biswas@vuse.vanderbilt.edu;Department of CS, SIUE, Edwardsville, IL 62026, USA. jweinbe@siue.edu

  • Venue:
  • Applied Intelligence
  • Year:
  • 2001

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Abstract

This paper discusses the design and implementation of an integrated diagnosis system, MDS (Multi-level Diagnosis System), which combines associational and model-based approaches to diagnosis. The design and implementation of the associational module is tailored to achieving efficiency in routine diagnostic problem solving, and to providing a desirable interface for the users. The model-based diagnosis module is developed to achieve completeness and consistency in the fault isolation task, and to avoid the brittleness that often occurs in associational systems. MDS addresses the important issue of combining the use of “deeper” knowledge in the form of a system model with “shallow” (or associational) knowledge, using a diagnostic controller to improve completeness and consistency without sacrificing efficiency. The diagnostic controller also employs a methodology for automated knowledge refinement by identifying incomplete and inconsistent rules and diagnostic tests in the associational module, and then by performing updates to correct the problems. This paper focuses on the design and implementation of the diagnostic controller.