Keith Paarporn - The distributed nature of multiagent systems leaves them susceptible to adversarial interference. A goal of a system operator is to allocate a limited number of security resources to minimize adversarial influence. Informational constraints and asymmetries impact how these resources should be distributed. In this talk, I illustrate this interplay in the setting of Colonel Blotto games, a class of competitive resource allocation games. We provide a generalized method to compute security strategies given asymmetric information between the competitors. We compare these solutions to a complete information set-up to identify the value of information in this setting. This analysis highlights the value of obfuscating information from an opponent. We then ask: Is it ever beneficial to announce one’s strategy to an opponent? We find this is never the case in a one-vs-one setting. However, we characterize a three-player setting where there is an incentive for one player to publicly announce part of its strategy. To conclude, we highlight the interplay between information, adversarial influence, and resilience in a dynamic networked multiagent scenario. We find there are inherent trade-offs between security and risk in designing resilient distributed algorithms for the network against adversarial influences. Dario Paccagnan - Modern society is based on large-scale engineered systems, often at the service of human end-users, e.g., transportation and power networks. While the control of such systems is typically grounded on purely engineering principles, their performance greatly depends on how human users interact with them. A common issue arising in these settings is the performance degradation often incurred when the users’ interests are not aligned to the “greater good” (e.g., traffic routing). In this context, a natural question arises: how can we design behavior-influencing mechanisms to incentivize efficient use of the existing infrastructure? In this presentation, I answer this question in relation to the well-studied class of congestion games, often used to model traffic assignment problems. More precisely, I show how to design mechanisms that utilize only local information, and robustly maximize the system efficiency. Surprisingly, optimal mechanisms designed using only local information perform closely to those designed using full information (1% difference for affine latency functions). Additionally, I show how the proposed approach recovers and generalizes a number of well-known results in the literature. Finally, I discuss how the marginal cost mechanism, known to be optimal in the continuous-flow approximation, results in a lower efficiency than that encountered if no mechanism was used. Guosong Yang - Cyber-physical systems (CPS) integrate digital communication, control, and computational functionalities with processes governed by the laws of physics. The inherent combination and interconnection of heterogeneous dynamics in CPS make their analysis and design a challenging task. My research addresses problems stemming from hybrid dynamics, networking, and information in control, which represent many of the major challenges in developing autonomous CPS. In this talk, I will share the motivation and contribution of our work on uncertainty quantification and control with limited information for CPS.
Keith Paarporn is currently a postdoctoral scholar in the Electrical and Computer Engineering Department at the University of California, Santa Barbara. He received his B.S. in Electrical Engineering from the University of Maryland, College Park in 2013, his M.S. in Electrical and Computer Engineering from the Georgia Institute of Technology in 2016, and his Ph.D. in Electrical and Computer Engineering from the Georgia Institute of Technology in 2018. His research interests include game theory and its application to networked systems in engineered, social, and biological domains. Dr. Dario Paccagnan is a Postdoctoral Fellow with the Mechanical Engineering Department and the Center for Control, Dynamical Systems and Computation, University of California, Santa Barbara. In 2018, he obtained a Ph.D. degree from the Information Technology and Electrical Engineering Department, ETH Z ̈urich, Switzerland. He received his B.Sc. and M.Sc. in Aerospace Engineering in 2011 and 2014 from the University of Padova, Italy. In 2014, he also received the M.Sc. in Mathematical Modelling from the Technical University of Denmark; all with Honors. Dr. Paccagnan was a visiting scholar at the University of California, Santa Barbara in 2017, and at Imperial College London, in 2014. He was awarded the ETH medal in recognition for an outstanding PhD dissertation, as well as the Early Postdoc Mobility Fellowship and the Doc Mobility Fellowship from the Swiss National Science Foundation. His interests are at the interface between distributed control and game theory, with a focus on the design of behavior-influencing mechanisms for socio-technical systems. Guosong Yang is currently a postdoctoral scholar in the Center for Control, Dynamical Systems, and Computation at the University of California, Santa Barbara, CA, USA, hosted by Prof. João P. Hespanha. He received a Ph.D. degree in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign, Urbana, IL, USA in 2017, advised by Prof. Daniel Liberzon. His research interests include switched and hybrid systems, networked control systems, learning in games, and applications to cyber-physical systems (CPS) and network security. His work has won the 2019 ACM SIGBED HSCC Best Paper Award.