Eugenio Bargiacchi graduated in 2011 with a B.Sc. in Computer Science at the Università Statale di Milano in Italy, and obtained his M.Sc. in Artificial Intelligence in 2016 at the University of Amsterdam. He has
started his PhD journey in 2017 in the AI Lab at the VUB under the supervision of Ann Nowé. In 2019 has joined the MOBI research centre, and has recently obtained an FWO grant for strategic basic research.
His research is based on model-based multi-agent reinforcement learning and the development for performant and sample-efficient methods of learning optimal policies in very large high-dimensional domains.
Stable MultI-agent LEarnIng for neTworks (SMILE-IT)
Machine learning for real-time Advanced Multi-Energy Trading (MAMuET)
Controlling Large Scale Multi-Agent Environments with Model-Based Reinforcement Learning