Knowledge Systems Laboratory
Stanford University

Abstract: The General Motors Variation-Reduction Adviser: Deployment Issues for an AI Application

The General Motors Variation-Reduction Adviser is a knowledge system built on case-based reasoning principles that is currently in use in over a dozen General Motors Assembly Centers. This paper reviews the overall characteristics of the system and then focuses on various AI elements critical to support its deployment to a production system. A key AI enabler is ontology-guided search using domain-specific ontologies.

This paper won an award at the innovative Applications of Arificial Intelligence in 2004 and was highlighted in the Emerging Trends for AI for the Media - AI News Bulletin Fall 2004. http://www.aaai.org/Pressroom/Bulletin/newsletter-04fall.html A slightly updated version was also published in the AI Magazine. Alexander P. Morgan, John A. Cafeo, Kurt Godden, Ronald M. Lesperance, andrea M. Simon, Deborah L. McGuinness, and James L. Benedict. the General Motors Variation-Reduction Adviser. AI Magazine 26:2 (2005). index.

Alexander P. Morgan, John A. Cafeo, Kurt Godden, Ronald M. Lesperance, Andrea M. Simon, Deborah L. McGuinness, and James L. Benedict. The General Motors Variation-Reduction Adviser: Deployment Issues for an AI Application. In the Proceedings of the Innovative Applications of Artificial Intelligence, San Jose, CA., July 2004. The word version is available. Additional diagrams augmenting the published version are also available.

Return to Selected Papers of Deborah L. McGuinness.