# Distributed Nash Equilibrium Seeking over Time-Varying Directed Communication Networks

@article{Nguyen2022DistributedNE, title={Distributed Nash Equilibrium Seeking over Time-Varying Directed Communication Networks}, author={Duong Thuy Anh Nguyen and Duong Tung Nguyen and Angelia Nedi'c}, journal={ArXiv}, year={2022}, volume={abs/2201.02323} }

We study distributed algorithms for finding a Nash equilibrium (NE) in a class of non-cooperative convex games under partial information. Specifically, each agent has access only to its own smooth local cost function and can receive information from its neighbors in a time-varying directed communication network. To this end, we propose a distributed gradient play algorithm to compute a NE by utilizing local information exchange among the players. In this algorithm, every agent performs a…

## 4 Citations

### AB/Push-Pull Method for Distributed Optimization in Time-Varying Directed Networks

- Mathematics
- 2022

In this paper, we study the distributed optimization problem for a system of agents embedded in time-varying directed communication networks. Each agent has its own cost function and agents cooperate…

### Ensuring both Accurate Convergence and Differential Privacy in Nash Equilibrium Seeking on Directed Graphs

- Computer ScienceArXiv
- 2022

An approach that can achieve both accurate convergence and rigorous differential privacy with cumulative privacy budget in distributed Nash equilibrium seeking is proposed, in sharp contrast to existing differential-privacy solutions for networked games that have to trade convergence accuracy for differential privacy.

### Differentially-private Distributed Algorithms for Aggregative Games with Guaranteed Convergence

- Computer Science, EconomicsArXiv
- 2022

This work proposes a fully distributed equilibrium-computation approach for aggregative games that can achieve both rigorous differential privacy and guaranteed computation accuracy of the Nash equilibrium, in sharp contrast to existing differential-privacy solutions.

### Ensure Differential Privacy and Convergence Accuracy in Consensus Tracking and Aggregative Games with Coupling Constraints

- Computer ScienceArXiv
- 2022

The generalized Nash equilibrium (GNE) seeking mechanism and the differential-privacy noise injection mechanism are co-designed and a new consensus-tracking algorithm is proposed that can achieve rigorous differential privacy while maintaining accurate tracking performance, which, to the authors' knowledge, has not been achieved before.

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