The Royal Tree Problem, a Benchmark for Single and Multi-population Genetic Programming

Introduction Given the multiplicity of GP programs that could produce the correct solution for a particular problem, it is difficult to judge the effectiveness of various architectural changes or parameter settings on the performance of a GP system. We encountered these problems directly in the design of our genetic programming tool lilgp. When lilgp was completed, we wanted to test how well it solved a set of standard GP problems. In fact, for a new GP system it is difficult to judge whether it is performing as intended or not, since the programs it generates are not necessarily identical to those generated by other GP systems. This raised two questions: what constitutes a "standard" problem in GP, and how do we rate the performance of a system on such a problem. One of the goals of this research was to create a benchmark problem to test how well a particular GP configuration would perform as compared to other configurations. Such benchmarks have existed for so