Milano, Nicola
Milano, Nicola
Istituto di Scienze e Tecnologie della Cognizione - ISTC
Interaction Rules Supporting Effective Flocking Behavior
2024 Milano, N.; Nolfi, S.
Qualitative differences between evolutionary strategies and reinforcement learning methods for control of autonomous agents
2024 Milano, N.; Nolfi, S.
Automated Categorization of Behavioral Quality Through Deep Neural Networks
2022 Pagliuca, P.; Milano, N.; Nolfi, S.
Phenotypic complexity and evolvability in evolving robots
2022 Milano, N.; Nolfi, S.
Automated curriculum learning for embodied agents a neuroevolutionary approach
2021 Milano, N.; Nolfi, S.
Autonomous learning of features for control: Experiments with embodied and situated agents
2021 Milano, N.; Nolfi, S.
Efficacy of Modern Neuro-Evolutionary Strategies for Continuous Control Optimization
2020 Pagliuca, Paolo; Milano, Nicola; Nolfi, Stefano
Moderate Environmental Variation Across Generations Promotes the Evolution of Robust Solutions
2019 Milano N.; Carvalho J.T.; Nolfi S.
Robustness, evolvability and phenotypic complexity: insights from evolving digital circuits
2019 Milano, N; Pagliuca, P; Nolfi, S
Evolving Robust Solutions for Stochastically Varying Problems
2018 Carvalho, Jonata Tyska; Milano, Nicola; Nolfi, Stefano
Maximizing adaptive power in neuroevolution
2018 Pagliuca, Paolo; Milano, Nicola; Nolfi, Stefano
Environmental Variations Promotes Adaptation in Artificial Evolution
2017 Milano, Nicola; Carvalho Jonata, Tyska; Nolfi, Stefano
Robustness to Faults Promotes Evolvability: Insights from Evolving Digital Circuits
2016 Milano, Nicola; Nolfi, Stefano