Abstract
Application of Genetic Programming to the discovery of empirical laws is often impaired by the huge size of the domains involved. In physical applications, dimensional analysis is a powerful way to trim out the size of these spaces This paper presents a way of enforcing dimensional constraints through formal grammars in the GP framework. As one major limitation for grammar-guided GP comes from the initialization procedure (how to find admissible and sufficiently diverse trees with a limited depth), an initialization procedure based on dynamic grammar pruning is proposed. The approach is validated on the problem of identification of a materials response to a mechanical test.
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Ratle, A., Sebag, M. (2000). Genetic Programming and Domain Knowledge: Beyond the Limitations of Grammar-Guided Machine Discovery. In: Schoenauer, M., et al. Parallel Problem Solving from Nature PPSN VI. PPSN 2000. Lecture Notes in Computer Science, vol 1917. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45356-3_21
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DOI: https://doi.org/10.1007/3-540-45356-3_21
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