发布时间：2017-03-10 编辑：admin 来源：华科自动化学院
报告题目：Reinforcement Learning for Resilient Control in Cooperative and Adversarial Multi-agent Networks
报告人：F. L. Lewis, National Academy of Inventors. Fellow IEEE, InstMC, and IFAC Moncrief-O’Donnell Endowed Chair and Head, Advanced Controls & Sensors Group, UTA Research Institute (UTARI), The University of Texas at Arlington, USA, Qian Ren Thousand Talents Consulting Professor, Northeastern University, Shenyang, China
报告摘要 : The interactions of multiple dynamical agents have applications in vehicle formation control, trust propagation in autonomous teams, synchronization phenomena in complex systems, aerospace and satellite coordination, and the relations of multiple interacting human-robotic systems. The relations between the local feedback control system design for each agent and the restrictions imposed by allowed communication topologies are intriguing and can result in either beneficial emergent behaviors or unexpected detrimental overall performance of the integrated autonomous team. The concept of Optimality provides an organizational principle for behavior that can be exploited to increase the resilience of multiple interacting dynamical agents in communication networks. In fact, it was shown by Charles Darwin that cognitive learning principles organized along the lines of optimality and resource conservation over long timescales are responsible for the phenomenon of Natural Selection of multiple species.
In this discussion we show that formulating team performance objectives in terms of optimality principles allows the unification of ideas from optimal control and adaptive control by using cognitive reinforcement learning principles. This leads to a new class of cognitive multi-agent controllers that allow each agent to learn optimal solutions online using real-time measurements of the actions of neighboring agents in the network. These ideas are rooted in Hamilton’s principle in classical mechanics and allow applications to cooperative multi-player graphical games. Applications are then made to cyberphysical systems, in particular to the resilient and efficient distributed control of renewable energy microgrids.
报告人简历： F.L. Lewis: Member, National Academy of Inventors. Fellow IEEE, Fellow IFAC, Fellow AAAS, Fellow U.K. Institute of Measurement & Control, PE Texas, U.K. Chartered Engineer. UTA Distinguished Scholar Professor, UTA Distinguished Teaching Professor, and Moncrief-O’Donnell Chair at The University of Texas at Arlington Research Institute. Qian Ren Thousand Talents Consulting Professor, Northeastern University, Shenyang, China. Foreign Expert Scholar, Huazhong University of Science and Technology. IEEE Control Systems Society Distinguished Lecturer. Bachelor's Degree in Physics/EE and MSEE at Rice University, MS in Aeronautical Engineering at Univ. W. Florida, Ph.D. at Ga. Tech. He works in feedback control, reinforcement learning, intelligent systems, and distributed control systems. He is author of 7 U.S. patents, 340 journal papers, 414 conference papers, 20 books, 48 chapters, and 12 journal special issues. He received the Fulbright Research Award, NSF Research Initiation Grant, ASEE Terman Award, Int. Neural Network Soc. Gabor Award 2009, U.K. Inst. Measurement & Control Honeywell Field Engineering Medal 2009. Received IEEE Computational Intelligence Society Neural Networks Pioneer Award 2012 and AIAA Intelligent Systems Award 2016. Distinguished Foreign Scholar at Nanjing Univ. Science & Technology. Project 111 Professor at Northeastern University, China. Distinguished Foreign Scholar at Chongqing Univ. China. Received Outstanding Service Award from Dallas IEEE Section, selected as Engineer of the Year by Ft. Worth IEEE Section. Listed in Ft. Worth Business Press Top 200 Leaders in Manufacturing. Received the 2010 IEEE Region 5 Outstanding Engineering Educator Award and the 2010 UTA Graduate Dean’s Excellence in Doctoral Mentoring Award. Elected to UTA Academy of Distinguished Teachers 2012. Texas Regents Outstanding Teaching Award 2013. He served on the NAE Committee on Space Station in 1995.