分布式约束优化

Distributed Constraint Optimization

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 System with intelligence,autonomy,as well as synergies,is concerned by people.Distributed constraint optimization is an effective technology which can coordinate a number of Agents to solve distributed problems.Firstly this paper introduces the basic concept and the framework of distributed optimization problem and sum up the existing solution to the problem.Then it will compare and analysis these algorithms through efficiency,performance,privacy,and other sides.And it will introduce some typical applications of distributed optimization problem.Finally it will discuss the future direction of research and development.