Comparing Subtree Crossover with Macromutation

In genetic programming, crossover swaps randomly selected subtrees between parents. Recent work in genetic algorithms ([13]) demonstrates that when one of the parents selected for crossover is replaced with a randomly generated parent, the algorithm performs as well or better than crossover for some problems. [13] termed this form of macromutation headless chicken crossover. The following paper investigates two forms of headless chicken crossover for manipulating parse trees and shows that both types of macromutation perform as well or better than standard subtree crossover. It is argued that these experiments support the hypothesis that the building block hypothesis is not descriptive of the operation of subtree crossover.

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