Receding Horizon Games for Safe and 
Fair Resource Allocation in Dynamic Settings

by

Sophie Hall

PhD Student | Automatic Control Laboratory (IfA) | ETH Zürich 

Tuesday, October 28
11 am - 12 pm
 Guggenheim 442

About the Seminar: 
Game-theoretic MPC (or Receding Horizon Games) is an emerging control methodology for multi-agent systems that generates control actions by solving a dynamic game with coupling constraints in a receding-horizon fashion. This control paradigm has recently received increasing attention in various application fields, including robotics, autonomous driving, traffic networks, and energy grids, due to its ability to model the competitive nature of self-interested agents with shared resources while incorporating future predictions, dynamic models, and constraints into the decision-making process.

In this talk, we will: (i) Motivate Receding Horizon Games through dynamic resource allocation problems (energy, water, traffic, etc.); (ii) Place it in the context of advanced MPC methods and explain why we need a game-theoretic perspective; (iii) Present the control framework and its solution concept based on variational Generalized Nash Equilibria, discussing assumptions necessary to ensure fair outcomes; (iv) Present novel insights on open-loop GNE trajectories using turnpike and dissipative theory,  and present stability certificates for safe closed-loop operation.
 

About the Speaker: 
Sophie Hall is a PhD student at the Automatic Control Laboratory (IfA) at ETH Zürich since May 2021, working in Prof. Dörfler's group. She studied Mechanical Engineering in undergraduate, with a specialization in medical engineering and control at the University of Surrey, UK, and Nanyang Technological University, Singapore. In 2021, she obtained MSc in Biomedical Engineering from ETH Zürich, where she specialized in modeling and control. During her master's studies, she conducted research on Gaussian processes and control in Prof. Zeilinger's group. For her master's thesis, completed in Prof. Dörfler's group, she worked on real-time gradient-based nonlinear MPC, analyzing the scheme's stability and applying it to anesthesia control.