11th IEEE Inter. Conference on Emerging Technologies and Factory Automation Reinforcement Learning in Multi-Agent Systems pdf (1.08MB) Robert Babuska Delft Center for Systems and Control, Delft University of Technology, The Netherlands. Abstract: Multi-agent systems are rapidly finding applications in a variety of domains, including robotics, distributed control, telecommunications, etc. Although the individual agents can be programmed in advance, many tasks require that they learn behaviors online. A significant part of the research on multi-agent learning concerns reinforcement learning techniques. This paper gives a survey of multi-agent reinforcement learning, starting with a review of the different viewpoints on the learning goal, which is a central issue in the field. Two generic goals are distinguished: stability of the learning dynamics, and adaptation to the other agents’ dynamic behavior. The focus on one of these goals, or a combination of both, leads to a categorization of the methods and approaches in the field. The challenges and benefits of multi-agent reinforcement learning are outlined along with open issues and future research directions. Robert Babuska Delft Center for Systems and Control, Delft University of Technology, The Netherlands.   Robert Babuska received the M.Sc. degree in control engineering from the Czech Technical University in Prague, in 1990, and the Ph.D. degree from the Delft University of Technology, the Netherlands, in 1997. He has had faculty appointments at the Technical Cybernetics Department of the Czech Technical University Prague and at the Electrical Engineering Faculty of the Delft University of Technology. Currently, he is a Professor at the Delft Center for Systems and Control, Faculty of Mechanical Engineering, Delft University of Technology. His research interests include neural and fuzzy systems for modeling and identification, fault-tolerant control, learning and adaptive control and dynamic multi-agent systems. He is involved in several projects in which these techniques are being applied in the fields of mechatronics, robotics and aerospace. Robert Babuska has co-authored over 190 publications, including one research monograph (Kluwer Academic Publishers), two edited books, 24 invited chapters in books, 48 journal papers and more than 120 conference papers. He has been serving as an associate editor of the IEEE Transactions on Fuzzy Systems, Engineering Applications of Artificial Intelligence, and as an area editor of Fuzzy Sets and Systems. He is the chairman of the IFAC Technical Committee on Cognition and Control.