Length bias and search limitations in cartesian genetic programming
Brian W. Goldman, William F. Punch · 2013
In this paper we examine how Cartesian Genetic Programming's (CGP's) method for encoding directed acyclic graphs (DAGs) and its mutation operator bias the effective length of individuals as well as the distribution of inactive nodes in the genome. We investigate these biases experimentally using two CGP variants as comparisons: Reorder, a method for shuffling node ordering without effecting individual evaluation, and DAG, a method for removing the concept of node position. Experiments were performed on four problems tailored to highlight potential search limitations, with further testing on the 3-bit multiplier problem.