Abstract
We present an innovative fuzzy-neural architecture that is able to automatically generate a knowledge base, in an extractable form, for use in hierarchical knowledge-based controllers. The knowledge base is in the form of a linguistic rule base appropriate for a fuzzy inference system. We modify Berenji and Khedkar's GARIC architecture [3] to a hierarchical controller and enable it to automatically generate a knowledge base. A pseudo-supervised learning scheme using reinforcement learning and error backpropagation is employed. Example applications are provided to underscore its viability.
Original language | English (US) |
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Pages (from-to) | 2625-2630 |
Number of pages | 6 |
Journal | Proceedings of the IEEE International Conference on Systems, Man and Cybernetics |
Volume | 4 |
State | Published - Dec 1 1996 |
Externally published | Yes |
Event | Proceedings of the 1996 IEEE International Conference on Systems, Man and Cybernetics. Part 4 (of 4) - Beijing, China Duration: Oct 14 1996 → Oct 17 1996 |
ASJC Scopus subject areas
- Control and Systems Engineering
- Hardware and Architecture