Is Novelty Search Good for Evolving Morphologically Robust Robot Controllers?

This study evaluates comparative behavioral search methods for evolutionary controller design in robot teams, where the goal is to evaluate the morphological robustness of evolved controllers. That is, where controllers are evolved for specific robot sensory-motor configurations (morphologies) but must continue to function as these morphologies degrade. Robots use neural controllers where behavior evolution is directed by developmental Neuro-Evolution (HyperNEAT). Guiding evolutionary controller design we use objective (fitness function) versus non-objective (novelty) search. The former optimizes for behavioral fitness and the latter for behavioral novelty. These search methods are evaluated across varying robot morphologies and increasing task complexity. Results indicate that both novelty and objective search evolve team controllers (behaviors) that are morphologically robust given degrading robot morphologies and increasing task complexity. Results thus suggest that novelty search is not necessarily suitable for generating robot team behaviors that are robust to changes in robot morphologies (for example, due to damaged or disabled sensors and actuators).