A partitioning-based task allocation strategy for Police Multi-Agents

被引：0

作者：

Liang Zhiwei ^{[1
]}

Yang Xiang ^{[1
]}

Deng Yao ^{[1
]}

机构：

[1] Nanjing Univ Posts & Telecommun, Coll Automat, Nanjing 210046, Peoples R China

来源：

26TH CHINESE CONTROL AND DECISION CONFERENCE (2014 CCDC) | 2014年

关键词：

RoboCup rescue; Multi-agent; Task allocation; Cluster;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

RCRSS (RoboCup Rescue Simulation System, RCRSS) is a typical multi-agent system. In order to solve the task allocation problem for police multi-agents of this system, this paper presents a novel partitioning-based task allocation strategy. It is carried out through the use of clustering, namely the K-means clustering algorithm, to divide the map into several regions. Then the dynamic adjustment system with static assignment was adopted synthetically for the implementation. The experimental results show that the new task allocation strategy for the police can adapt to a variety of disaster environments and improve the efficiency of multi-agent collaboration.

引用

页码：2124 / 2128

页数：5

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