Compound derivations in fuzzy genetic programming

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 initializing a population,; incorporating a priori knowledge; the new genetic operator compound which provides an alternative to lambda abstraction; and proving speedup theorems