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A fuzzy model for learning in automata

Published online by Cambridge University Press:  09 March 2009

Ashoke Kumar Datta
Ashoke Kumar Datta
Affiliation:
Electronics and Communication Sciences Unit, Indian Statistical Institute, 203, Barrack pore Trunk Road, Calcutta 700035 (India).
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Summary

A simple general model for learning, using a fuzzy set theoretic approach and fuzzy decision in an automaton which has nonfuzzy input/output, is proposed. The process has been modelled somewhat in the fashion of general biological systems, which may be viewed as a fuzzy decision process where learning consists in taking a tentative action and reinforcing the membership values on the basis of the results of that action. The model is tested on an automaton whose sole purpose is to follow the boundary on an object with which it makes contact during its movements. The automaton is simulated by a computer. it has standard 8–neighbourhood configuration with binary sense capability and three action capabilities. The automaton has been found to learn to take correct action in a large number of possible input situations within only a few thousand moves.

Information

Type
Article
Information
Robotica , Volume 3 , Issue 1 , January 1985 , pp. 39 - 44
Copyright
Copyright © Cambridge University Press 1985

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