文件名称：分步实现搜索
文件大小：168KB
文件格式：PDF
更新时间：2018-09-16 10:58:26
分布式，搜索
This note considers multi-agent systems seeking to optimize a convex ag-gregate function. We assume that the gradient of this function is distributed, mean-ing that each agent can compute its corresponding partial derivative with informa-tion about its neighbors and itself only. In such scenarios, the discrete-time imple-mentation of the gradient descent method poses the basic challenge of determining appropriate agent stepsizes that guarantee the monotonic evolution of the objective function. We provide a distributed algorithmic solution to this problem based on the aggregation of agent stepsizes via adaptive convex combinations. Simulations illustrate our results.