Genetic Programming and Domain Knowledge: Beyond the limitations of grammar-guided Machine Discovery - Archive ouverte HAL
Communication Dans Un Congrès Année : 2000

Genetic Programming and Domain Knowledge: Beyond the limitations of grammar-guided Machine Discovery

Alain Ratle
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Michèle Sebag
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Résumé

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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hal-00116116 , version 1 (20-08-2021)

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Alain Ratle, Michèle Sebag. Genetic Programming and Domain Knowledge: Beyond the limitations of grammar-guided Machine Discovery. International Conference on Parallel Problem Solving from Nature, 2000, Paris, France. pp.211-220, ⟨10.1007/3-540-45356-3_21⟩. ⟨hal-00116116⟩
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