Demonstrating constraints to diversity with a tunably difficult problem for genetic programming

This work introduces a tunably difficult problem for genetic programming (GP) that probes for an upper bound to the amount of heterogeneity that can be represented by a single individual. Although GP´s variable-length representation would suggest that there is no upper bound, our results indicate otherwise. The results provide insight into the dynamics that occur during the course of a GP run.