Cutting evaluation costs: An investigation into early termination in genetic programming

Genetic programming is very computationally intensive, particularly in CPU time. A number of approaches to evaluation cost reduction have been proposed, among them early termination of evaluation (applicable in problem domains where estimates of the final fitness value are available during evaluation). Like all cost reduction techniques, early termination balances overall computation cost against the risk of finding worse solutions. We evaluate the influence of various properties of the problem domain-problem class, reliability of fitness estimates, trajectory of fitness estimates, and evolutionary trajectory-to determine whether any is able to predict the effects of early termination. There is little correlation with any of these, with one exception. Boolean problems see little change in running time, and hence only small changes in performance, are distinguished by both problem class, and each of the other metrics.