Proceedings of the 10th Annual Conference Companion on Genetic and Evolutionary Computation 2008
DOI: 10.1145/1388969.1389043
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Potential fitness for genetic programming

Abstract: We introduce potential fitness, a variant of fitness function that operates in the space of schemata and is applicable to tree-based genetic programing. The proposed evaluation algorithm estimates the maximum possible gain in fitness of an individual's direct offspring. The value of the potential fitness is calculated by analyzing the context semantics and subtree semantics for all contexts (schemata) of the evaluated tree. The key feature of the proposed approach is that a tree is rewarded for the correctly c… Show more

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