Abstract
In search, optimisation and simulation applications, model building is largely manual. However, it may be automated if a complete enough body of data is available. The objective of the present work is to generate models for use in decision support.
In the following we shall concentrate on the method, namely genetic programming, suitable for our problem. A review of genetic programming and a description of an implementation of a tool for symbolic regression is given. Limited experimental results are reported and future improvements to the tool are also discussed.
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Salhi, A., Glaser, H., De Roure, D. (1996). Model Generation Using Genetic Programming. In: Jesshope, C., Shafarenko, S. (eds) UK Parallel ’96. Springer, London. https://doi.org/10.1007/978-1-4471-1504-5_7
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DOI: https://doi.org/10.1007/978-1-4471-1504-5_7
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