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JACIII Vol.3 No.5 pp. 341-347
doi: 10.20965/jaciii.1999.p0341
(1999)

Paper:

Rule Extraction by Structural Learning with an Immediate Critic

Masumi Ishikawa

Department of Brain Science and Engineering Graduate School of Life Science and Systems Engineering Kyushu Institute of Technology 680-4 Kawazu, Iizuka, Fukuoka 820-8502, Japan

Received:
May 7, 1999
Accepted:
June 20, 1999
Published:
October 20, 1999
Keywords:
Rule extraction, Learning with an immediate critic, Reinforcement learning, Supervised learning, Structural learning
Abstract

Studies on rule extraction using neural networks have exclusively adopted supervised learning, in which correct outputs are always given as training samples. The real world, however, does not always provide correct answers. We advocate the use of learning with an immediate critic, which is simple reinforcement learning. It uses an immediate binary reinforcement signal indicating whether or not an output is correct. This, of course, makes learning more difficult and time-consuming than supervised learning. Learning with an immediate critic alone, however, is not powerful enough in extracting rules from data because distributed representation emerges just as in back propagation learning. We propose to combine learning with an immediate critic and structural learning with forgetting (SLF) – structural learning with an immediate critic and forgetting (SLCF). A procedure of rule extraction from data by SLCF is similar to that by SLF. Applications of the proposed method to rule extraction from lenses data demonstrate its effectiveness.

Cite this article as:
Masumi Ishikawa, “Rule Extraction by Structural Learning with an Immediate Critic,” J. Adv. Comput. Intell. Intell. Inform., Vol.3, No.5, pp. 341-347, 1999.
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