This survey paper studies deterministic control systems that integrate three of the most active
research areas during the last years:(1) online learning control systems,(2) distributed …

Multi-time scale techniques based on singular perturbations and averaging theory are
among the most powerful tools developed for the synthesis and analysis of feedback control …

Game dynamics have been widely used as learning and computational tool to find
evolutionarily stable strategies. Nevertheless, most of the existing evolutionary game …

How to design tolls that induce socially optimal traffic loads with dynamically arriving
travelers who make selfish routing decisions? We propose a two-timescale discrete-time …

The contents of this book comprise an appropriate background to start working and doing
research on mean-field-type control and game theory. To make the exposition and …

We consider a problem of robust estimation over a network in an errors-in-variables context.
Each agent measures noisy samples of a local pair of signals related by a linear regression …

In this article, we study the optimal design of High Occupancy Toll (HOT) lanes. In our setup,
the traffic authority determines the road capacity allocation between HOT lanes and ordinary …

We ask if it is possible to positively influence social behavior with no risk of unintentionally
incentivizing pathological behavior. In network routing problems, if network traffic is …

Traffic congestion has dire economic and social impacts in modern metropolitan areas. To
address this problem, in this paper we introduce a novel type of model-free transactive …

How can the system operator learn an incentive mechanism that achieves social optimality
based on limited information about the agents' behavior, who are dynamically updating their …