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Deep Reinforcement Learning for Multi-Agent Interaction
Our group specialises in developing machine learning algorithms for autonomous systems control in multi-agent systems, with a particular focus on deep reinforcement learning. Questions we tackle include: How can multiple agents learn together to solve a given task in a scalable and robust way? How can a single agent learn to collaborate effectively in a team in which other agents may have diverse types and may enter/leave at any time? I will also give a glimpse into our research with UK-based company Five AI on developing safe, interpretable planning and prediction algorithms for autonomous driving in urban environments.
Bio: Dr. Stefano V. Albrecht is Lecturer (Assistant Professor) in Artificial Intelligence in the School of Informatics at the University of Edinburgh. He leads the Autonomous Agents Research Group (https://agents.inf.ed.ac.uk) which currently consists of 14 members that conduct research into developing machine learning algorithms for autonomous systems. Dr. Albrecht is a Royal Society Industry Fellow working with a team at UK-based company Five AI (https://www.five.ai) to develop AI technologies for autonomous vehicles. Previously, Dr. Albrecht was a postdoctoral fellow at the University of Texas at Austin working with Prof. Peter Stone. 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.