Strategic Decision-Making and Learning for Autonomous Agents


Game theoretic models have proven to be powerful to gain insight into the processes of strategic decision-making and learning among interacting autonomous agents. I present a review of some fundamental concepts, emerging research, and open problems related to the analysis and control of evolutionary games, with particular emphasis on applications in social, economic, biological and robotic networks. In populations of autonomous agents, when individuals' self-interested goals conflict with the greater interest of the group, counter-intuitive outcomes and social dilemmas may arise. Evolutionary game theory has emerged as a vital tool set in the investigation of such network dynamics. In addition, one may explore how agents might learn to choose their strategies over time to adapt with the peers and surroundings; control theorists are particularly interested in knowing whether a small group of agents can manipulate the collective actions at large. Hence, decision-making, learning and control can be discussed in a unified framework, leading to new challenges and research opportunities for control scientists and engineers.


Ming Cao is a professor of systems and control with the Engineering and Technology Institute (ENTEG) at the University of Groningen, the Netherlands. He received the Bachelor degree in 1999 and the Master degree in 2002 from Tsinghua University, Beijing, China, and the Ph.D. degree in 2007 from Yale University, New Haven, CT, USA, all in Electrical Engineering. From September 2007 to August 2008, he was a Postdoctoral Research Associate with the Department of Mechanical and Aerospace Engineering at Princeton University, Princeton, NJ, USA. He worked as a research intern during the summer of 2006 with the Mathematical Sciences Department at the IBM T. J. Watson Research Center, NY, USA. He is the 2017 and inaugural recipient of the Manfred Thoma medal from the International Federation of Automatic Control (IFAC) and the 2016 recipient of the European Control Award sponsored by the European Control Association (EUCA). He is a Senior Editor for Systems and Control Letters, and an Associate Editor for IEEE Transactions on Automatic Control, IEEE Transactions on Circuits and Systems and IEEE Circuits and Systems Magazine. He is a member of the IFAC Conference Board, and a vice chair of the IFAC Technical Committee on Large-Scale Complex Systems. His research interests include autonomous agents and multi-agent systems, complex networks and decision-making processes.