Publication Type

Conference Proceeding Article

Publication Date

7-1991

Abstract

This paper outlines a methodology for analyzing the representational support for knowledge-based decision-modeling in a broad domain. A relevant set of inference patterns and knowledge types are identified. By comparing the analysis results to existing representations, some insights are gained into a design approach for integrating categorical and uncertain knowledge in a context sensitive manner.

Discipline

Artificial Intelligence and Robotics | Computer Sciences

Research Areas

Intelligent Systems and Decision Analytics

Publication

Uncertainty in Artificial Intelligence: Proceedings of the Seventh Conference: July 13-15, 1991, University of California, Los Angeles

First Page

212

Last Page

219

ISBN

9781558602038

Publisher

Morgan Kaufmann

City or Country

San Mateo

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://worldcat.org/isbn/9781558602038

Share

COinS