Convergence of Ant Colony Multi-Agent Swarms

被引：1
作者：
Ornia, Daniel Jarne [1 ]
Mazo, Manuel, Jr. [1 ]
机构：
[1] Delft Univ Technol, DCSC, Delft, Netherlands
来源：
PROCEEDINGS OF THE 23RD INTERNATIONAL CONFERENCE ON HYBRID SYSTEMS: COMPUTATION AND CONTROL (HSCC2020) (PART OF CPS-IOT WEEK) | 2020年
关键词：
swarm robotics; ant colony; random walk; convergence; OPTIMIZATION; SYSTEM;
D O I：
10.1145/3365365.3382199
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Ant Colony algorithms are a set of biologically inspired algorithms used commonly to solve distributed optimization problems. Convergence has been proven in the context of optimization processes, but these proofs are not applicable in the framework of robotic control. In order to use Ant Colony algorithms to control robotic swarms, we present in this work more general results that prove asymptotic convergence of a multi-agent Ant Colony swarm moving in a weighted graph.
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页数：11
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