Research
My main research interests are:
Reinforcement Learning
Novelty Search and Quality Diversity Algorithms
AI Embodiement and the study of Emergent behaviors
The complete list of my publications can be found on one of these sites:
Selected Publications
G. Paolo, J. Gonzalez-Billandon, B. Kégl, "A Call for Embodied AI", ICML 2024 Position paper track, ArXiv link
G. Paolo, "Learning in Sparse Rewards settings through Quality-Diversity algorithms", 2022, ArXiv link, PhD Thesis
G. Paolo, A. Coninx, A. Laflaquière, S. Doncieux, "Discovering and Exploiting Sparse Rewards in a Learned Behavior Space", Evolutionary Computation Journal MIT Press, 2024, ArXiv link
G. Paolo, A. Coninx, S. Doncieux, A. Laflaquière, "Sparse Reward Exploration via Novelty Search and Emitters", The Genetic and Evolutionary Computation Conference (GECCO) 2021, ArXiv link. Nominated for best paper award in the CS track.
G. Paolo, A. Laflaquière, A. Coninx, S. Doncieux, "Unsupervised Learning and Exploration of Reachable Outcome Space", 2020 IEEE International Conference on Robotics and Automation (ICRA), ArXiv link
L. Tai, G. Paolo, M. Liu, "Virtual-to-real deep reinforcement learning: Continuous control of mobile robots for mapless navigation", 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) , ArXiv link
