一种计算强拟非膨胀映射族公共不动点的分布式算法

Ji Liu, D. Fullmer, A. Nedić, T. Başar, A. Morse
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引用次数: 6

摘要

本文研究了m > 1个非线性映射族Mi:∈n→∈n的一个公共不动点的分布式算法,该算法假定每个映射都是强拟非扩张的,并且至少存在一个这样的公共不动点。一个公共不动点由m个智能体同时递归地计算,假设每个智能体i只知道Mi,它的邻居生成的不动点的当前估计,仅此而已。邻居关系用一个时变的有向图来描述,其顶点对应于agent,其弧线描述邻居关系。结果表明,对于任意序列的重复联合强连接邻居图_1 (t), t∈{1,2,…},该算法使所有智能体的估计收敛到Mi的一个公共不动点,i∈{1,2,…,m}。
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A distributed algorithm for computing a common fixed point of a family of strongly quasi-nonexpansive maps
This paper studies a distributed algorithm for finding a common fixed point of a family of m > 1 nonlinear maps Mi: ℝn → ℝn assuming that each map is strongly quasi-nonexpansive, and that at least one such common fixed point exists. A common fixed point is simultaneously and recursively computed by m agents assuming that each agent i knows only Mi, the current estimates of the fixed point generated by its neighbors, and nothing more. Neighbor relationships are described by a time-varying directed graph ℕ(t) whose vertices correspond to agents and whose arcs depict neighbor relationships. It is shown that for any sequence of repeatedly jointly strongly connected neighbor graphs ℕ(t), t ∈ {1, 2, …}, the algorithm causes all agents' estimates to converge to a common fixed point of Mi, i ∈ {1, 2, …, m}.
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