Continuous-time integral dynamics for Aggregative Game equilibrium seeking
For researchers in game theory and distributed control, this work offers an improved convergence condition for aggregative game equilibrium seeking.
This paper proposes continuous-time semi-decentralized dynamics for equilibrium computation in aggregative games, using decentralized projected-gradient dynamics driven by an integral control law. It proves global exponential convergence and derives a sufficient condition that improves on established results.
In this paper, we consider continuous-time semi-decentralized dynamics for the equilibrium computation in a class of aggregative games. Specifically, we propose a scheme where decentralized projected-gradient dynamics are driven by an integral control law. To prove global exponential convergence of the proposed dynamics to an aggregative equilibrium, we adopt a quadratic Lyapunov function argument. We derive a sufficient condition for global convergence that we position within the recent literature on aggregative games, and in particular we show that it improves on established results.