Active leading through obstacles using ant-colony algorithm

被引：8
|
作者：
Vatankhah, Ramin [2 ]
Etemadi, Shahram [1 ]
Alasty, Aria [2 ]
Vossoughi, Gholam-Reza [2 ]
Boroushaki, Mehrdad [2 ]
机构：
[1] Islamic Azad Univ, Sci & Res Branch, Dept Mech & Aerosp Engn, Tehran, Iran
[2] Sharif Univ Technol, Sch Mech Engn, CEDRA, Tehran, Iran
来源：
NEUROCOMPUTING | 2012年 / 88卷
关键词：
Multi-agents; Active leader; Fast flocking; Ant colony algorithm; FLOCKING; AGENTS; CONNECTIVITY; COORDINATION; OPTIMIZATION; DESIGN; SWARMS;
D O I：
10.1016/j.neucom.2011.08.030
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In presence of obstacles, inter-agent pulling actions must be bounded. In this case, to remain connected to the group, the leader-agent (LA) must perform an active leading strategy. In this paper, an active leading algorithm is proposed which monitors the neighborhood of the LA and adjusts its velocity. The algorithm is based on the ant colony optimization (ACO) technique. As a real time optimization package, the ACO algorithm maximizes influence of the LA on the group, leading to fast flocking. Comparison with another optimization method is provided as well. Simulations show that the algorithm is successful and cost effective. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码：67 / 77
页数：11
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