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Speaker: Stefano V. Albrecht (University of Edinburgh)
Title: Deep Reinforcement Learning for Multi-Agent Interaction
Abstract: Our group specialises in developing machine learning algorithms for autonomous systems control, with a particular focus on deep reinforcement learning and multi-agent reinforcement learning. We have a focus on problems of optimal decision making, prediction, and coordination in multi-agent systems. In this talk, I will give an overview of our research agenda along with some recent published papers in these areas, including our ongoing R&D work with Dematic to develop multi-agent RL solutions for large-scale multi-robot warehouse applications. I will also present some of our research done at UK-based self-driving company Five AI (acquired by Bosch in 2022) on robust and interpretable motion planning and prediction for autonomous driving.
Bio: Dr. Stefano V. Albrecht is Associate Professor of Artificial Intelligence in the School of Informatics, University of Edinburgh, where he leads the Autonomous Agents Research Group (https://agents.inf.ed.ac.uk). Dr. Albrecht is a Royal Society Industry Fellow working with Five AI/Bosch to develop AI technologies for autonomous vehicles; and he is a Royal Academy of Engineering Industrial Fellow working with KION/Dematic to develop reinforcement learning solutions for multi-robot warehouse systems. His research on reinforcement learning and multi-agent interaction has been published in leading conferences and journals for AI/ML/robotics, including NeurIPS, ICML, ICLR, IJCAI, AAAI, UAI, AAMAS, AIJ, JAIR, JMLR, TMLR, ICRA, IROS, T-RO. Previously, Dr. Albrecht was a postdoctoral fellow at the University of Texas at Austin. He obtained PhD and MSc degrees in Artificial Intelligence from the University of Edinburgh, and a BSc degree in Computer Science from Technical University of Darmstadt. He is co-author of the book "Multi-Agent Reinforcement Learning: Foundations and Modern Approaches" (MIT Press) which is available at https://marl-book.com.