6 papers
Learning Generalized Nash Equilibria in Non-Monotone Games with Quadratic Costs
Tatiana Tatarenko, Lucas Wey Hacker
We study generalized Nash equilibrium (GNE) problems in games with quadratic costs and individual linear equality constraints. Departing from approaches that require strong monoton…
Distributed Nash Equilibrium Seeking in Non-Monotone Games over the Simplex
Tatiana Tatarenko, S. Rasoul Etesami
In this work, we present a novel characterization of approximate Nash equilibria in a class of convex games over the simplex. To achieve this, we regularize the utility functions u…
Convergence Rate of Generalized Nash Equilibrium Learning in Strongly Monotone Games with Linear Constraints
Tatiana Tatarenko, Maryam Kamgarpour
We consider payoff-based learning of a generalized Nash equilibrium (GNE) in multi-agent systems. Our focus is on games with jointly convex constraints of a linear structure and st…
Fast Distributed Nash Equilibrium Seeking in Monotone Games
Tatiana Tatarenko, Angelia Nedich
This work proposes a novel distributed approach for computing a Nash equilibrium in convex games with merely monotone and restricted strongly monotone pseudo-gradients. By leveragi…
Huber Loss-Based Penalty Approach to Problems with Linear Constraints
Angelia Nedich, Tatiana Tatarenko
We consider a convex optimization problem with many linear inequality constraints. To deal with a large number of constraints, we provide a penalty reformulation of the problem, wh…
Accelerating Distributed Nash Equilibrium Seeking
Tatiana Tatarenko, Angelia Nedich
This work proposes a novel distributed approach for computing a Nash equilibrium in convex games with restricted strongly monotone pseudo-gradients. By leveraging the idea of the c…