Theory of Endorsements and Reasoning With Uncertainty, January 1984 - January 1986
Abstract
By emphasizing the sources of uncertainty and its consequences, an intelligent reasoning system shows the ability to plan a course of action appropriate to one's uncertainty, the ability to explain one's actions. and the ability to determine degree of belief in alternatives given evidence. Other than numerical inferences and reason maintenance, another approach to parallel certainty inference, the theory of endorsements, is presented. The fundamental assumption of the theory of endorsements is that subjective degrees of belief are composites of reasons to believe and disbelieve (positive and negative endorsements). Two implementations of the theory of endorsements, SOLOMON and HMM, are briefly described. GRANT, a knowledge system that finds sources of funding for research proposals, was developed to explore the utility of semantic matching in uncertain domains. The basic mode of inference used in GRANT is plausible inference.
Document Details
- Document Type
- Technical Report
- Publication Date
- Nov 01, 1987
- Accession Number
- ADA213262
Entities
People
- Alvah David
- David Day
- Jeff Delisio
- Mike Greenberg
- Paul R. Cohen
Organizations
- University of Massachusetts Amherst