Abstract

Intelligent and coordinated unmanned aerial vehicle (UAV) swarm combat will be the main mode of warfare in the future, and mechanistic design of autonomous cooperation within swarms is the key to enhancing combat effectiveness. Exploration of the essential features and patterns of autonomous collaboration in unmanned swarms has become the focus of scientific research and technological applications, in keeping with the evolving conceptions of the military theatre. However, given the unique attributes of the military and the novelty of the warfare mode of unmanned swarms, few achievements have been reported in the existing research. In this study, we analysed the military requirements of unmanned swarm operations and proposed an analytic framework for autonomous collaboration. Then, a literature review addressing swarm evolution dynamics, game-based swarm collaboration, and collaborative evolution on complex networks was conducted. Next, on the basis of the above work, we designed a community network for unmanned swarm cooperation and constructed a collaborative evolution model based on the multiplayer public goods game (PGG). Furthermore, according to the “network” and “model”, the dynamic evolution process of swarm collaboration was formally deduced. Finally, a simulation was conducted to analyse the influence of relevant parameters (i.e., swarm size, degree distribution, cost, multiplication factor) on the collaborative behaviour of unmanned swarms. According to the simulation results, some reasonable suggestions for collaborative management and control in swarm operation are given, which can provide theoretical reference and decision-making support for the design of coordination mechanisms and improved combat effectiveness in unmanned swarm operation.

Details

Title
A game-based approach for designing a collaborative evolution mechanism for unmanned swarms on community networks
Author
Wu, Zhonghong 1 ; Pan, Li 2 ; Yu, Minggang 3 ; Liu, Jintao 3 ; Mei, Dan 4 

 Naval University of Engineering, Weaponry Engineering College, Wuhan, China (GRID:grid.472481.c) (ISNI:0000 0004 1759 6293) 
 Naval University of Engineering, Electronics Engineering College, Wuhan, China (GRID:grid.472481.c) (ISNI:0000 0004 1759 6293) 
 Army Engineering University of PLA, Institute of Command and Control Engineering, Nanjing, China (GRID:grid.440614.3) (ISNI:0000 0001 0702 1566) 
 Naval Aviation University, Qingdao Campus, Qingdao, China (GRID:grid.440614.3) 
Publication year
2022
Publication date
2022
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2732927523
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.