Via San Martino della Battaglia 44 - oo185 Rome - Italy
Born in Naples (1989) I hold a Master degree in Physics released from the University of Naples Federico II and a PHD in Computer Science (robotics and neural system) released from University of Plymouth. Since 2015 I am a researchear at the Laboratory of Autonomous Robots and Artificial Life of the Institute of Cognitive Sciences and Technologies, my research activities focus on: evolutionary computation, genetic programming, reinforcement learning, evolutionary robotics, neural networks .
Milano, N. and Nolfi, S., 2020. Enhancing Cartesian genetic programming through preferential selection of larger solutions. Evolutionary Intelligence, pp.1-8.
Milano, N., Pagliuca, P. and Nolfi, S., 2019. Robustness, evolvability and phenotypic complexity: insights from evolving digital circuits. Evolutionary Intelligence, 12(1), pp.83-95.
Milano, N., Carvalho, J.T. and Nolfi, S., 2019. Moderate environmental variation across generations promotes the evolution of robust solutions. Artificial life, 24(4), pp.277-295.
Pagliuca, P., Milano, N. and Nolfi, S., 2018. Maximizing adaptive power in neuroevolution. PloS one, 13(7).
Milano, N. and Nolfi, S., 2016. Robustness to faults promotes evolvability: Insights from evolving digital circuits. PloS one, 11(7).
Milano, N., Carvalho, J.T. and Nolfi, S., 2017. Environmental variations promotes adaptation in artificial evolution. In 2017 IEEE Symposium Series on Computational Intelligence (SSCI) (pp. 1-7). IEEE.
Carvalho, J.T., Milano, N. and Nolfi, S., 2018, July. Evolving Robust Solutions for Stochastically Varying Problems. In 2018 IEEE Congress on Evolutionary Computation (CEC) (pp. 1-8). IEEE.