Andreas Malikopoulos
Cornell University
Seminar Information
Team theory provides a mathematical framework for decentralized stochastic control problems in which members cooperate to achieve a common objective while making decisions with different information. A fundamental challenge is signaling, through which a member’s decisions both affect the physical system and convey private information to other members. In this talk, I will present structural results for sequential dynamic team decision problems with nonclassical information structures and their dynamic programming decomposition. For each team member, with the other members’ strategies fixed, I will establish an information-state formulation whose update does not depend on that member’s control-strategy map. These results lead to parameterized dynamic programs in which the optimization is over control decisions rather than control laws, while the member’s realized information remains a parameter of the decomposition. I will then present a Bellman performance identity that characterizes the difference between the cost of an admissible strategy and the corresponding dynamic programming lower bound, and establishes conditions under which a member attains an optimal response. Finally, I will characterize when optimal decisions derived using the aggregate information of the team can be implemented by individual members using their own information states. Under appropriate implementability and attainment conditions, I will show that the centralized and team-member decompositions attain the same optimal value. These results clarify the relationship between information structure, decentralized implementation, and team optimality.
Andreas A. Malikopoulos is a Professor in the School of Civil and Environmental Engineering and the Director of the Information and Decision Science Laboratory at Cornell University. He also holds courtesy appointments with the Applied Mathematics, Systems Engineering, Cornell Robotics, Mechanical and Aerospace Engineering, and Electrical and Computer Engineering. His research is at the intersection of learning and control, with an emphasis on team theory and decentralized stochastic control. His contributions include structural results for team decision problems and decentralized frameworks that integrate decision-theoretic principles with learning for multi-agent coordination. His work seeks to establish the theoretical foundations for autonomous systems and teams that learn from their operation, coordinate their decisions, and interact with people and their physical environment under uncertainty. He connects these theoretical foundations with engineering practice, with particular emphasis on automotive applications and emerging mobility systems, including connected and automated vehicles. Before joining Cornell, he was the Terri Connor Kelly and John Kelly Career Development Professor in the Department of Mechanical Engineering and the founding Director of the Sociotechnical Systems Center at the University of Delaware. He previously served as Deputy Director of the Urban Dynamics Institute at Oak Ridge National Laboratory, which he joined as an Alvin M. Weinberg Fellow, and as a Senior Researcher at General Motors Global Research & Development. He received his Diploma in Mechanical Engineering from the National Technical University of Athens, Greece, in 2000, and his M.S. and Ph.D. degrees in Mechanical Engineering from the University of Michigan, Ann Arbor, in 2004 and 2008, respectively. Dr. Malikopoulos’ honors include the 2019 IEEE Intelligent Transportation Systems Young Researcher Award, the 2020 University of Delaware College of Engineering Outstanding Junior Faculty Award, the 2026 Cornell University Faculty Excellence in Mentoring Postdoctoral Scholars Award, and the 2026 IEEE Intelligent Transportation Systems Outstanding Application Award. His research with his students has been recognized with best paper and outstanding student paper awards, as well as several finalist distinctions. He was selected by the National Academy of Engineering to participate in the 2010 German-American Frontiers of Engineering Symposium and to organize a transportation session at the 2016 European-American Frontiers of Engineering Symposium. He was also selected as a 2012 Kavli Frontiers of Science Scholar by the National Academy of Sciences. He serves as an Associate Editor of Automatica and IEEE Transactions on Automatic Control and as a Senior Editor of IEEE Transactions on Intelligent Transportation Systems. He is a Fellow of ASME, a Senior Member of IEEE, and a member of the Board of Governors and a Distinguished Lecturer of the IEEE Intelligent Transportation Systems Society.