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Automatic construction of reactive control systems using symbolic machine learning

Published online by Cambridge University Press:  07 July 2009

Claude Sammut
Claude Sammut
Affiliation:
Department of Artificial Intelligence, University of New South Wales, Sydney, NSW 2052, Australia (email: claude@cse. unsw.edu.au)
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Abstract

This paper reviews a number of applications of machine learning to industrial control problems. We take the point of view of trying to automatically build rule-based reactive systems for tasks that, if performed by humans, would require a high degree of skill, yet are generally performed without thinking. Such skills are said to be sub-cognitive. While this might seem restrictive, most human skill is executed subconsciously and only becomes conscious when an unfamiliar circumstance is encountered. This kind of skill lends itself well to representation by a reactive system, that is, one that does not create a detailed model of the world, but rather, attempts to match percepts with actions in a very direct manner.

Type
Research Article
Information
The Knowledge Engineering Review , Volume 11 , Issue 1 , March 1996 , pp. 27 - 42
Copyright
Copyright © Cambridge University Press 1996

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