论文标题
异步分布式和可扩展的广义NASH平衡，以寻求强烈单调游戏的算法
An asynchronous distributed and scalable generalized Nash equilibrium seeking algorithm for strongly monotone games
论文作者
论文摘要
在本文中，我们提出了三种分布式算法，以解决一类普遍的NASH平衡（GNE），以寻求强烈单调游戏的问题。第一个（SD-GENO）基于代理的同步更新，而第二个和第三个（Ad-Geed and Ad-Geno）代表异步解决方案，这些解决方案对通信延迟具有鲁棒性。 Ad-Geno可以看作是ADGEED的完善，因为它仅需要节点辅助变量，从而增强算法的可扩展性。我们的主要贡献是通过操作者理论方法证明与游戏的变异gne相聚。最后，我们将算法应用于网络Cournot游戏，并显示不同的激活序列和延迟如何影响收敛。我们还将所提出的算法与文献（Adagnes）中唯一的其他算法进行了比较，并观察到Ad-Geno的表现优于替代方案。
In this paper, we present three distributed algorithms to solve a class of generalized Nash equilibrium (GNE) seeking problems in strongly monotone games. The first one (SD-GENO) is based on synchronous updates of the agents, while the second and the third (AD-GEED and AD-GENO) represent asynchronous solutions that are robust to communication delays. AD-GENO can be seen as a refinement of AD-GEED, since it only requires node auxiliary variables, enhancing the scalability of the algorithm. Our main contribution is to prove converge to a variational GNE of the game via an operator-theoretic approach. Finally, we apply the algorithms to network Cournot games and show how different activation sequences and delays affect convergence. We also compare the proposed algorithms to the only other in the literature (ADAGNES), and observe that AD-GENO outperforms the alternative.
