Concept formation using ITERATE building rule models for efficient reasoning

Gautam Biswas; Gyesung Lee; J. B. Weinberg

doi:10.1117/12.141724

23 March 1993 Concept formation using ITERATE building rule models for efficient reasoning

Gautam Biswas, Gyesung Lee, J. B. Weinberg

Proceedings Volume 1963, Applications of Artificial Intelligence 1993: Knowledge-Based Systems in Aerospace and Industry; (1993) https://doi.org/10.1117/12.141724
Event: Optical Engineering and Photonics in Aerospace Sensing, 1993, Orlando, FL, United States

Abstract

This paper discusses the application of a conceptual clustering algorithm called ITERATE to improve complex problem solving. More specifically, we apply the ITERATE system to build a hierarchy of rule models from sets of rules defined for PLAYMAKER, an expert system for characterizing hydrocarbon fields and plays in terms of their essential geological characteristics for the purposes of prospect analysis. PLAYMAKER is built on MIDST, an expert system shell that employs task-specific reasoning structures. The rule model hierarchy derived by ITERATE is then used with the task-specific reasoning structures to develop a more efficient and focused reasoning mechanism. A set of case studies were conducted to demonstrate the improved performance of the reasoning system.

Citation Download Citation

Gautam Biswas, Gyesung Lee, and J. B. Weinberg "Concept formation using ITERATE building rule models for efficient reasoning", Proc. SPIE 1963, Applications of Artificial Intelligence 1993: Knowledge-Based Systems in Aerospace and Industry, (23 March 1993); https://doi.org/10.1117/12.141724

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