论文标题
在非Convex合作聚合游戏中实现社会最佳游戏：一种分布式随机退火方法
Achieving Social Optimum in Non-convex Cooperative Aggregative Games: A Distributed Stochastic Annealing Approach
论文作者
论文摘要
本文设计了一种非凸件合作构成游戏的分布式随机退火算法，其代理的成本功能不仅取决于代理人自己的决策变量，而且还依赖于代理商的决策变量总和。为了寻求合作汇总游戏的社会最佳选择，提出了分布式随机退火算法的分布式随机退火算法，其中当地成本功能是非convex，而代理之间的通信拓扑是时间变化。进一步分析了算法的社会最佳最佳融合。给出了一个数值示例来说明所提出的算法的有效性。
This paper designs a distributed stochastic annealing algorithm for non-convex cooperative aggregative games, whose agents' cost functions not only depend on agents' own decision variables but also rely on the sum of agents' decision variables. To seek the the social optimum of cooperative aggregative games, a distributed stochastic annealing algorithm is proposed, where the local cost functions are non-convex and the communication topology between agents is time varying. The weak convergence to the social optimum of the algorithm is further analyzed. A numerical example is given to illustrate the effectiveness of the proposed algorithm.
