Finding needles in haystacks is harder with neutrality

摘要

This research presents an extended analysis of the reported successes of the Cartesian Genetic Programming method on a simplified form of the Boolean parity problem. We show the method of sampling used by the CGP is significantly less effective at locating solutions than the solution density of the corresponding formula space would warrant. We present results indicating that the loss of performance is caused by the sampling bias of the CGP, due to the neutrality friendly representation. We implement a simple intron free random sampling algorithm which performs considerably better on the same problem and then explain how such performance is possible.