Created by W.Langdon from gp-bibliography.bib Revision:1.4891

- @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, genetic algorithms, grammar, k-bounded context-free languages, lambda abstraction, machine-learning method, nonlinear transformations, speedup theorems, context-free languages, fuzzy logic, genetic algorithms, 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