报告人：Dario Paccagnan UC Santa Barbara, USA
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 is- sue 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, of- ten 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.
Dr. Dario Paccagnan is a Postdoctoral Fellow with the Mechanical Engineer- ing 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 Zu ?rich, 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.