4 papers
The Dynamic of Body and Brain Co-Evolution
Paolo Pagliuca, Stefano Nolfi
We introduce a method that permits to co-evolve the body and the control properties of robots. It can be used to adapt the morphological traits of robots with a hand-designed morph…
Efficacy of Modern Neuro-Evolutionary Strategies for Continuous Control Optimization
Paolo Pagliuca, Nicola Milano, Stefano Nolfi
We analyze the efficacy of modern neuro-evolutionary strategies for continuous control optimization. Overall, the results collected on a wide variety of qualitatively different ben…
Robust Optimization through Neuroevolution
Paolo Pagliuca, Stefano Nolfi
We propose a method for evolving solutions that are robust with respect to variations of the environmental conditions (i.e. that can operate effectively in new conditions immediate…
Robustness, Evolvability and Phenotypic Complexity: Insights from Evolving Digital Circuits
Nicola Milano, Paolo Pagliuca, Stefano Nolfi
We show how the characteristics of the evolutionary algorithm influence the evolvability of candidate solutions, i.e. the propensity of evolving individuals to generate better solu…