论文部分内容阅读
多Agent系统由于拥有智能性、自主性以及协同性等一系列的特性受到人们广泛的关注.分布式约束优化是协调多个Agent解决分布问题的有效技术,目前是多Agent领域的研究热点.本文将首先介绍分布式约束优化问题的基本概念和框架结构,总结现有的解决该问题的主要算法.并通过效率、性能、隐私等各方面对这些算法进行全面的比较与分析,然后介绍分布式约束优化问题的一些典型应用,最后还将对分布式约束优化问题及其算法未来的研究发展方向进行论述.
Multi-Agent systems are widely concerned by a series of features such as intelligence, autonomy and cooperation.Distributed constrained optimization is an effective technique to coordinate multiple Agents to solve distribution problems and is currently a hotspot in the field of Multi-Agent. We will first introduce the basic concepts and framework of the distributed constrained optimization problem and summarize the main existing algorithms to solve this problem.All these aspects are compared and analyzed in terms of efficiency, performance and privacy, and then the distribution Some typical applications of constrained optimization problems, and finally will discuss the research direction of distributed constrained optimization and its algorithms in the future.