Conference Paper

Adjudicated GP: A Behavioural Approach to Selective Breeding

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For some time, there has been a realisation among Genetic Programming researchers that relying on a single scalar fitness value to drive evolutionary search is no longer a satisfactory approach. Instead, efforts are being made to gain richer insights into the complexity of program behaviour. To this end, particular attention has been focused on the notion of semantic space. In this paper we propose and unified hierarchical approach which decomposes program behaviour into semantic, result and adjudicated spaces, where adjudicated space sits at the top of the behavioural hierarchy and represents an abstraction of program behaviour that focuses on the success or failure of candidate solutions in solving problem sub-components. We show that better, smaller solutions are discovered when crossover is directed in adjudicated space. We investigate the effectiveness of several possible adjudicated strategies on a variety of classification and symbolic regression problems, and show that both of our novel pillage and barter tactics significantly outperform both a standard genetic programming and an enhanced genetic programming configuration on the fourteen problems studied. The proposed method is extremely effective when incorporated into a standard Genetic Programming structure but should also complement several other semantic approaches proposed in the literature.

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ffl The tree has never been executed, ffl The tree has never been executed in a test sub sequence which subsequently failed a consistency check (nak) and it is anticipated that it would not be executed by any of the fitness test cases that have not been used (unknown). However a tree may be selected as the crossover location immediately if either:-- ffl The number of times it was used in a test subsequence which subsequently passed its consistency check (ok) is less than nak, or 1 W. B. Langdon 17 August 1995 2 ffl both it has never been run successfully and unknown is zero. Otherwise, the following ratio is calculated: nak + unknown ok + unknown (1) When ratios for three trees have been calculated, crossover occurs in the tree with the highest ratio. If 100 t
Size fair and homologous crossover genetic operators for tree based genetic programming are described and tested. Both produce considerably reduced increases in program size and no detrimental effect on GP performance. GP search spaces are partitioned by the ridge in the number of program v. their size and depth. A ramped uniform random initialisation is described which straddles the ridge. With subtree crossover trees increase about one level per generation leading to sub-quadratic bloat in length. 1 INTRODUCTION It has been known for some time that programs within GP populations tend to rapidly increase in size as the population evolves. If unchecked this consumes excessive machine resources. This is usually addressed either by enforcing a size or depth limit on the programs or by an explicit size penalty in the fitness measure, although other techniques may be used. Both main approaches have problems. It has been shown that the protective effect of inviable code (which...
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