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Genetic programming for prediction and control

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Abstract

The relatively ‘new’ field of genetic programming has received a lot of attention during the last few years. This is because of its potential for generating functions which are able to solve specific problems. This paper begins with an extensive overview of the field, highlighting its power and limitations and providing practical tips and techniques for the successful application of genetic programming in general domains. Following this, emphasis is placed on the application of genetic programming to prediction and control. These two domains are of extreme importance in many disciplines. Results are presented for an oral cancer prediction task and a satellite attitude control problem. Finally, the paper discusses how the convergence of genetic programming can be significantly speeded up through bulk synchronous model parallelisation.

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Authors and Affiliations

  1. Department of Information Systems and Computing, Brunel University, UB8 3PH, Uxbridge, Middlesex, UK

    D. C. Dracopoulos & S. Kent

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  1. D. C. Dracopoulos
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  2. S. Kent
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Dracopoulos, D.C., Kent, S. Genetic programming for prediction and control. Neural Comput & Applic 6, 214–228 (1997). https://doi.org/10.1007/BF01501508

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