Discovering the influences of complex network effects on recovering large scale multiagent systems

探索复杂网络效应对大规模多智能体系统恢复的影响

阅读:1

Abstract

Building efficient distributed coordination algorithms is critical for the large scale multiagent system design, and the communication network has been shown as a key factor to influence system performance even under the same coordination protocol. Although many distributed algorithm designs have been proved to be feasible to build their functions in the large scale multiagent systems as claimed, the performances may not be stable if the multiagent networks were organized with different complex network topologies. For example, if the network was recovered from the broken links or disfunction nodes, the network topology might have been shifted. Therefore, their influences on the overall multiagent system performance are unknown. In this paper, we have made an initial effort to find how a standard network recovery policy, MPLS algorithm, may change the network topology of the multiagent system in terms of network congestion. We have established that when the multiagent system is organized as different network topologies according to different complex network attributes, the network shifts in different ways. Those interesting discoveries are helpful to predict how complex network attributes influence on system performance and in turn are useful for new algorithm designs that make a good use of those attributes.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。