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In this paper we examine the behaviour of the uniform crossover and point mutation GP operators [12] on the even-η-parity problem for η = 3;4; 6 and present a novel representation of function nodes, designed to allow the search operators to make smaller movements around the solution space. Using this representation, performance on the even-6-parity problem is improved by three orders of magnitude...
We consider a form of phenotype plasticity in Genetic Programming (GP). This takes the form of a set of real-valued numerical parameters associated with each individual, an optimisation (or learning) algorithm for adapting their values, and an inheritance strategy for propagating learned parameter values to offspring. We show that plastic GP has significant benefits including faster evolution and...
Sub-machine-code GP (SMCGP) is a technique to speed up genetic programming (GP) and to extend its scope based on the idea of exploiting the internal parallelism of sequential CPUs. In previous work [20] we have shown examples of applications of this technique to the evolution of parallel programs and to the parallel evaluation of 32 or 64 fitness cases per program execution in Boolean classification...
We describe a Genetic Algorithm called Grammatical Evolution (GE) that can evolve complete programs in an arbitrary language using a variable length linear genome. The binary genome determines which production rules in a Backus Naur Form grammar definition are used in a genotype to phenotype mapping process to a program. Expressions and programs of arbitrary complexity may be evolved using this system...
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