NASA Logo

NTRS

NTRS - NASA Technical Reports Server

Back to Results
Mathematical algorithms for approximate reasoningMost state of the art expert system environments contain a single and often ad hoc strategy for approximate reasoning. Some environments provide facilities to program the approximate reasoning algorithms. However, the next generation of expert systems should have an environment which contain a choice of several mathematical algorithms for approximate reasoning. To meet the need for validatable and verifiable coding, the expert system environment must no longer depend upon ad hoc reasoning techniques but instead must include mathematically rigorous techniques for approximate reasoning. Popular approximate reasoning techniques are reviewed, including: certainty factors, belief measures, Bayesian probabilities, fuzzy logic, and Shafer-Dempster techniques for reasoning. A group of mathematically rigorous algorithms for approximate reasoning are focused on that could form the basis of a next generation expert system environment. These algorithms are based upon the axioms of set theory and probability theory. To separate these algorithms for approximate reasoning various conditions of mutual exclusivity and independence are imposed upon the assertions. Approximate reasoning algorithms presented include: reasoning with statistically independent assertions, reasoning with mutually exclusive assertions, reasoning with assertions that exhibit minimum overlay within the state space, reasoning with assertions that exhibit maximum overlay within the state space (i.e. fuzzy logic), pessimistic reasoning (i.e. worst case analysis), optimistic reasoning (i.e. best case analysis), and reasoning with assertions with absolutely no knowledge of the possible dependency among the assertions. A robust environment for expert system construction should include the two modes of inference: modus ponens and modus tollens. Modus ponens inference is based upon reasoning towards the conclusion in a statement of logical implication, whereas modus tollens inference is based upon reasoning away from the conclusion. These algorithms allow one to reason accurately with uncertain data. The above environment can replicate state-f-the-art expert system environments which provides a continuity between the current expert systems which cannot be validated or verified and future expert systems which should be both validated and verified
Document ID
19880020034
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Authors
Murphy, John H.
(Westinghouse Research and Development Center Pittsburgh, PA, United States)
Chay, Seung C.
(Westinghouse Research and Development Center Pittsburgh, PA, United States)
Downs, Mary M.
(Westinghouse Research and Development Center Pittsburgh, PA, United States)
Date Acquired
September 5, 2013
Publication Date
August 1, 1988
Publication Information
Publication: NASA, Marshall Space Flight Center, Second Conference on Artificial Intelligence for Space Applications
Subject Category
Computer Programming And Software
Accession Number
88N29418
Distribution Limits
Public
Copyright
Public Use Permitted.

Available Downloads

There are no available downloads for this record.
No Preview Available