View article

An adaptive method for fitness evaluation is described that dynamically guides genetic programming to grow and prune program trees. The method is based on the minimum description length principle and evolves parsimonious solutions while preventing premature convergence. The effectiveness of the adaptive fitness functions is shown by evolving neural programs for modeling technical and environmental systems.