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Adaptive learning of process control and profit optimization using a classifier system

Gilbert, A. H., Bell, Frances and Mumford, Christine Lesley 1995. Adaptive learning of process control and profit optimization using a classifier system. Evolutionary Computation 3 (2) , pp. 177-198.

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Abstract

A classifier system is used to learn control and profit optimization of a batch chemical reaction. Ability to learn different market conditions and changes to reaction parameters is demonstrated. The profit sharing algorithm is used for apportionment of credit. The greater effectiveness of the use of the genetic algorithm over apportionment of credit alone or the random replacement of low strength rules is also shown. The classifier system is unusual in having more than one action per rule.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Additional Information: This article was originally published in Evolutionary Computation, Vol 3 no 2 (1995), pp. 177-198
Publisher: MIT Press
ISSN: 1063-6560
Related URLs:
Last Modified: 04 Jun 2017 04:03
URI: http://orca.cf.ac.uk/id/eprint/31858

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