Created by W.Langdon from gp-bibliography.bib Revision:1.4868
We also present a comprehensive study of the importance of semantic context of a sub-tree in tree based systems and introduce a novel context aware evaluation technique for evaluating sub-trees in context. The usefulness of this technique is demonstrated on a benchmark problem.
In this work, we introduce a new constructive and context aware crossover for GP, Context-Aware crossover, which works by placing the selected sub- trees in their best possible context in any tree. This is a greedy approach and results in an improved performance. It is tested on a wide range of problems and showed better performance on all the problems except the Uni-Variate and Bi-Variate Polynomial Symbolic Regression problems. Furthermore, the results show that it generates very compact form of trees without adversely affecting their fitness.
Finally, we show the usefulness of the context aware evaluation technique in encapsulating useful trees at the end of a run and using them to create a module repository. This repository is later used to improve the performance of the second cascaded run. For the second run, a variant of context-aware crossover is introduced, Context-Aware mutation which works on module repository. The effectiveness of this setup is demonstrated by re-examining a real world blood flow problem and improving the previously published results.",
Genetic Programming entries for Hammad Majeed