Expert system using deep knowledge and shallow knowledge

Details Expert system using deep knowledge and shallow knowledge Expert system using deep knowledge and shallow knowledge

1989-02-14

1990-07-03

Ruggiero, Joseph

Boots, shoes, and leggings

3642743, 36491793, G06F 1518

Patent

active

049396803

ABSTRACT:
An expert system infers by using deep knowledge and shallow knowledge. The deep knowledge may be physical rules which are basically satisfied in an electrical circuit which is an object of inference, and the shallow knowledge may be assumption knowledge derived from expert experience relating to the electrical circuit. The deep knowledge includes structure information of the object of inference and equation information representing behavior of the object. The structure of the shallow knowledge, which includes a concluding equation derived by omitting a portion of the equation of the deep knowledge, a conditional equation representing a condition under which the concluding equation is satisfied and the omitted item, is made essentially similar to the structure of the deep knowledge so that both the deep knowledge and the shallow knowledge are uniformly handled in one inference process.

REFERENCES:
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patent: 4658370 (1987-04-01), Erman et al.
patent: 4847784 (1989-07-01), Clancey
Real-Time Expert Systems in Process Control, Computing and Control Division (Colloquium), 11/29/85.
P. J. Hayes, "The Naive Physics Manifesto", in Michie D. (ed.) Expert Systems in the Micro-Electronic Age, Edinburgh University Press, 1979, pp. 242-270.
Chuck Rieger and Milt Grinberg, "The Declarative Representation and Procedural Simulation of Causality in Physical Mechanisms", Proc. of IJCAI-77, 1977, pp. 250-256.
Toyoaki Nishida, "Qualitative Reasoning-Formal Models of Commonsense Reasoning", Journal of Japanese Society for Artificial Intelligence, vol. 12, No. 1, 1987, pp. 30-43.
Takahira Yamaguchi et al., "Basic Design of Knowledge Compiler Based on Deep Knowledge", Journal of Japanese Society for Artificial Intelligence, vol. 2, No. 3, 1987, pp. 333-340.
Tom M. Mitchell et al., "Explanation-Based Generalization: A Unifying View", Machine Learning 1: 47-80, 1986, pp. 47-80.

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