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首页> 外文期刊>Neural Networks and Learning Systems, IEEE Transactions on >Distributed Generalized Nash Equilibrium Seeking Algorithm Design for Aggregative Games Over Weight-Balanced Digraphs
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Distributed Generalized Nash Equilibrium Seeking Algorithm Design for Aggregative Games Over Weight-Balanced Digraphs

机译:权重有向图的聚合博弈分布式广义纳什均衡算法设计

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摘要

In this paper, two aggregative games over weight-balanced digraphs are studied, where the cost functions of all players depend on not only their own decisions but also the aggregate of all decisions. In the first problem, the cost functions of players are differentiable with Lipschitz gradients, and the decisions of all players are coupled by linear coupling constraints. In the second problem, the cost functions are nonsmooth, and the decisions of all players are constrained by local feasibility constraints as well as linear coupling constraints. In order to seek the variational generalized Nash equilibrium (GNE) of the differentiable aggregative games, a continuous-time distributed algorithm is developed via gradient descent and dynamic average consensus, and its exponential convergence to the variational GNE is proven with the help of Lyapunov stability theory. Then, another continuous-time distributed projection-based algorithm is proposed for the nonsmooth aggregative games based on differential inclusions and differentiated projection operations. Moreover, the convergence of the algorithm to the variational GNE is analyzed by utilizing singular perturbation analysis. Finally, simulation examples are presented to illustrate the effectiveness of our methods.
机译:在本文中,研究了两个权重有向图的聚合博弈,其中所有参与者的成本函数不仅取决于他们自己的决策,还取决于所有决策的总和。在第一个问题中,参与者的成本函数与Lipschitz梯度是可微的,并且所有参与者的决策都受到线性耦合约束的耦合。在第二个问题中,成本函数不平滑,所有参与者的决策都受到本地可行性约束以及线性耦合约束的约束。为了寻求可微集合博弈的变分广义纳什均衡(GNE),通过梯度下降和动态平均共识开发了一种连续时间分布式算法,并借助Lyapunov稳定性证明了其对变分GNE的指数收敛性。理论。然后,基于差分包含和差分投影操作,提出了一种针对非光滑集合博弈的另一种基于连续时间分布式投影的算法。此外,利用奇异摄动分析,分析了算法对变分GNE的收敛性。最后,通过仿真实例说明了我们方法的有效性。

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