On Effective and Inexpensive Local Search Techniques in Genetic Programming Regression

Local search methods can harmoniously work with global search methods such as Evolutionary Algorithms (EAs); however, particularly in Genetic Programming (GP), concerns remain about the additional cost of local search (LS). One successful such system is Chameleon, which tunes internal GP nodes and addresses cost concerns by employing a number of strategies to make its LS both effective and inexpensive. Expense is reduced by an innovative approach to parsimony pressure whereby smaller trees are rewarded with local search opportunities more often than bigger trees.

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