activity
20172024
most citedRobust Optimization through Neuroevolution

25 citations · 26 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV2024

A Computer Vision-Based Quality Assessment Technique for the automatic control of consumables for analytical laboratories

Meriam Zribi, Paolo Pagliuca, Francesca Pitolli

The rapid growth of the Industry 4.0 paradigm is increasing the pressure to develop effective automated monitoring systems. Artificial Intelligence (AI) is a convenient tool to imp…

cs.NE2023

Learning and evolution: factors influencing an effective combination

Paolo Pagliuca

The mutual relationship between evolution and learning is a controversial argument among the artificial intelligence and neuro-evolution communities. After more than three decades,…

cs.RO2020

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…

cs.NE2019★ 1 cited

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…

cs.NE2018★ 25 cited

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…

cs.NE2017

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…