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Temporal and contextual knowledge in model-based expert systems

Author
Heher, Dennis
Published
Nov 1, 1987.
Physical Description
1 electronic document
Additional Creators
Toth-Fejel, Tihamer
Online Version

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Unclassified, Unlimited, Publicly available.
Free-to-read Unrestricted online access
Summary
A basic paradigm that allows representation of physical systems with a focus on context and time is presented. Paragon provides the capability to quickly capture an expert's knowledge in a cognitively resonant manner. From that description, Paragon creates a simulation model in LISP, which when executed, verifies that the domain expert did not make any mistakes. The Achille's heel of rule-based systems has been the lack of a systematic methodology for testing, and Paragon's developers are certain that the model-based approach overcomes that problem. The reason this testing is now possible is that software, which is very difficult to test, has in essence been transformed into hardware.
Other Subject(s)
Collection
NASA Technical Reports Server (NTRS) Collection.
Note
Document ID: 19880006981.
Accession ID: 88N16363.
NASA. Marshall Space Flight Center, Third Conference on Artificial Intelligence for Space Applications, Part 1; p 15-19.
Terms of Use and Reproduction
No Copyright.
View MARC record | catkey: 15695962