Speaker: Anna Nagurney, University of Massachusetts
Bio: Anna Nagurney is the Eugene M. Isenberg Chair in Integrative Studies and was appointed to this endowed chaired professorship in the Department of Operations and Information Management in the Isenberg School of Management at the University of Massachusetts Amherst on April 14, 2021. Prior to that, she was the John F. Smith Memorial Professor of Operations Management, since 1998. She is also the Founding Director of the Virtual Center for Supernetworks and the Supernetworks Laboratory for Computation and Visualization at UMass Amherst. She is an Affiliated Faculty Member of the Department of Civil and Environmental Engineering and the Department of Mechanical and Industrial Engineering at UMass Amherst. She received her AB, ScB, ScM, and PhD degrees from Brown University in Providence, Rhode Island. She devotes her career to education and research that combines operations research/management science, engineering, and economics. Her focus is the applied and theoretical aspects of network systems, particularly in the areas of transportation and logistics, critical infrastructure, and in economics and finance.
Talk Title: Labor and Supply Chain Networks: Insights from Models Inspired by the COVID-19 Pandemic
Abstract: The COVID-19 pandemic has dramatically illustrated the importance of labor in supply chain networks in numerous economic sectors, from agriculture to healthcare. In this talk, I will discuss our recent research on the inclusion on labor in supply chains both in optimization and game theory frameworks to elucidate the impacts of disruptions of labor in terms of availability as well as productivity on product flows, prices, as well as the profits of firms. I will also highlight what can be done to ameliorate negative impacts and will also discuss the power of setting appropriate wages on supply chain links from production and transportation to storage and ultimate distribution to points of demand. I will conclude with some of our experiences in influencing policy in the pandemic.
Speaker: Marco Scarsini, LUISS, Italy
Bio: Marco Scarsini is a professor in the Department of Economics and Finance at LUISS, Rome, Italy. His research interests include applied probability and game theory, with a current focus on congestion games and social learning.
Talk Title: Price of Anarchy in Congestion Games: Beyond Worst-Case
Abstract: We consider the behavior of the price of anarchy in congestion as a function of some parameters of the model. The first part of the talk will focus on nonatomic congestion games and will examine the price of anarchy as a function of the traffic demand. First we will show that both in light and heavy traffic the price of anarchy is close to one under very mild conditions on the cost functions (no condition on the network is needed). Then we will examine the central region of the demand. This analysis is more complex and both the cost functions and the network have an influence of the price of anarchy. In the second part we will consider atomic congestion games where each player takes part in the game with some exogenous probability (not necessarily equal for different players). We will show that the price of anarchy is an increasing function of the maximum p of these probabilities and goes from 4/3 when p=0 to 5/2 when p=1.
Speaker: Jason Marden, University of California, Santa Barbara
Bio: Jason R. Marden is a Full Professor in the Department of Electrical and Computer, Engineering at the University of California, Santa Barbara. Jason received a BS in Mechanical Engineering in 2001 from UCLA, and a PhD in Mechanical Engineering in 2007, also from UCLA, under the supervision of Jeff S. Shamma, where he was awarded the Outstanding Graduating PhD Student in Mechanical Engineering. After graduating from UCLA, he served as a junior fellow in the Social and Information Sciences Laboratory at the California Institute of Technology until 2010 when he joined the University of Colorado. In 2015, Jason joined the Department of Electrical and Computer Engineering at the University of California, Santa Barbara.
Jason is a recipient of the ONR Young Investigator Award (2015), NSF Career Award (2014), the AFOSR Young Investigator Award (2012), the American Automatic Control Council Donald P. Eckman Award (2012), and the SIAM/SGT Best Sicon Paper Award (2015). Furthermore, Jason is also an advisor for the students selected as finalists for the best student paper award at the IEEE Conference on Decision and Control (2011, 2016, 2017) and American Control Conference (2020). Jason’s research interests focus on game theoretic methods for the control of distributed multiagent systems.
Talk Title: Mechanism Design for Multiagent Coordination
Abstract: The goal in networked control of multiagent systems is to derive desirable collective behavior through the design of local control algorithms. The information available to the individual agents, either through sensing or communication, invariably defines the space of admissible control laws. Hence, informational restrictions impose constraints on the achievable performance guarantees. This talk will focus on how agents should utilize available information to optimize the efficiency of the emergent collective behavior. In particular, we will discuss a methodology for optimizing the efficiency guarantees (i.e., price of anarchy) in distributed resource allocation problems through the design of local agent objective functions. We will then demonstrate the implications of this result in both engineering and societal systems. One particular illustration focuses on the design of taxation mechanisms to optimize the price of anarchy in atomic congestion games. Here, our findings provide the optimal taxation mechanisms and price of anarchy guarantees for such settings.
