Distributed Nash Equilibrium Seeking for Monotone Generalized Noncooperative Games by a Regularized Penalty Method
arXiv:2010.13078 · doi:10.1109/TCYB.2021.3087663
Abstract
In this work, we study the distributed Nash equilibrium seeking problem for monotone generalized noncooperative games with set constraints and shared affine inequality constraints. A distributed regularized penalty method is proposed. The idea is to use a differentiable penalty function with a time-varying penalty parameter to deal with the inequality constraints. A time-varying regularization term is used to deal with the ill-poseness caused by the monotonicity assumption and the time-varying penalty term. The asymptotic convergence to the least-norm variational equilibrium of the game is proven. Numerical examples show the effectiveness and efficiency of the proposed algorithm.
References in corpus (10)
- Discontinuous Dynamical Systems: A tutorial on solutions, nonsmooth analysis, and stability
- Distributed Nash equilibrium seeking for aggregative games with coupled constraints
- A distributed primal-dual algorithm for computation of generalized Nash equilibria with shared affine coupling constraints via operator splitting methods
- Real and Complex Monotone Communication Games
- Distributed GNE seeking under partial-decision information over networks via a doubly-augmented operator splitting approach
- Dynamic NE Seeking for Multi-Integrator Networked Agents with Disturbance Rejection
- Distributed Learning for Stochastic Generalized Nash Equilibrium Problems
- Distributed generalized Nash equilibria computation of monotone games via a preconditioned proximal point algorithm
- A Distributed Nash Equilibrium Seeking in Networked Graphical Games
- Inducing strong convergence of trajectories in dynamical systems associated to monotone inclusions with composite structure