Genetic Programming and Domain Knowledge: Beyond the Limitations of Grammar-Guided Machine Discovery

Created by W.Langdon from gp-bibliography.bib Revision:1.8129

@InProceedings{RatlePPSN2000,

• author = "Alain Ratle and Michele Sebag",
• title = "Genetic Programming and Domain Knowledge: Beyond the Limitations of Grammar-Guided Machine Discovery",
• booktitle = "Parallel Problem Solving from Nature - PPSN VI 6th International Conference",
• editor = "Marc Schoenauer and Kalyanmoy Deb and G{\"u}nter Rudolph and Xin Yao and Evelyne Lutton and Juan Julian Merelo and Hans-Paul Schwefel",
• year = "2000",
• publisher = "Springer Verlag",
• address = "Paris, France",
• month = "16-20 " # sep,
• pages = "211--220",
• series = "LNCS",
• volume = "1917",
• keywords = "genetic algorithms, genetic programming, context-free grammars",
• URL = "http://www.lri.fr/~sebag/REF/PPSN00.ps",
• URL = "http://citeseer.ist.psu.edu/377863.html",
• DOI = "doi:10.1007/3-540-45356-3_21",
• 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.",

}

Genetic Programming entries for Alain Ratle Michele Sebag

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