Compound Derivations in Fuzzy Genetic Programming

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@InProceedings{GeyerSchulz96e,

• author = "Andreas Geyer--Schulz",
• title = "Compound Derivations in Fuzzy Genetic Programming",
• booktitle = "1996 Biennial Conference of the North American Fuzzy Information Processing Society, NAFIPS",
• year = "1996",
• month = jul,
• pages = "510--514",
• DOI = "doi:10.1109/NAFIPS.1996.534787",
• keywords = "genetic algorithms, genetic programming, a priori knowledge, compound derivations, context-free language, equivalence transformations, fuzzy genetic programming, grammar, k-bounded context-free languages, lambda abstraction, machine-learning method, nonlinear transformations, speedup theorems, context-free languages, fuzzy logic, grammars, heuristic programming, learning (artificial intelligence)",
• size = "5 pages",
• abstract = "We introduce the concept of compound derivations in fuzzy genetic programming as an alternative to lambda abstraction. We show that in fuzzy genetic programming based on simple genetic algorithms over k-bounded context-free languages compound derivations provide a powerful tool for generating automatically equivalence transformations on the grammar of a context-free language. Although such transformations do not change the language generated by the grammar, the probability of generating words can be transformed almost at will. We apply this property to: nonlinear transformations of the probability of generating words for initialising a population,; incorporating a priori knowledge; the new genetic operator compound which provides an alternative to lambda abstraction; and proving speedup theorems",

}

Genetic Programming entries for Andreas Geyer-Schulz

Citations