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On-line Access: 2022-01-24

Received: 2020-07-17

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Xiaochen WU




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Frontiers of Information Technology & Electronic Engineering  2022 Vol.23 No.1 P.86-100


Dynamic grouping of heterogeneous agents for exploration and strike missions

Author(s):  Chen CHEN, Xiaochen WU, Jie CHEN, Panos M. PARDALOS, Shuxin DING

Affiliation(s):  School of Automation, Beijing Institute of Technology, Beijing 100081, China; more

Corresponding email(s):   xiaofan@bit.edu.cn, wsygdhrwxc@sina.com, pardalos@ufl.edu

Key Words:  Multi-agent, Dynamic missions, Group formation, Heuristic rule, Networking overhead

Chen CHEN, Xiaochen WU, Jie CHEN, Panos M. PARDALOS, Shuxin DING. Dynamic grouping of heterogeneous agents for exploration and strike missions[J]. Frontiers of Information Technology & Electronic Engineering, 2022, 23(1): 86-100.

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author="Chen CHEN, Xiaochen WU, Jie CHEN, Panos M. PARDALOS, Shuxin DING",
journal="Frontiers of Information Technology & Electronic Engineering",
publisher="Zhejiang University Press & Springer",

%0 Journal Article
%T Dynamic grouping of heterogeneous agents for exploration and strike missions
%A Chen CHEN
%A Xiaochen WU
%A Shuxin DING
%J Frontiers of Information Technology & Electronic Engineering
%V 23
%N 1
%P 86-100
%@ 2095-9184
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%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2000352

T1 - Dynamic grouping of heterogeneous agents for exploration and strike missions
A1 - Chen CHEN
A1 - Xiaochen WU
A1 - Jie CHEN
A1 - Panos M. PARDALOS
A1 - Shuxin DING
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 23
IS - 1
SP - 86
EP - 100
%@ 2095-9184
Y1 - 2022
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.2000352

The ever-changing environment and complex combat missions create new demands for the formation of mission groups of unmanned combat agents. This study aims to address the problem of dynamic construction of mission groups under new requirements. Agents are heterogeneous, and a group formation method must dynamically form new groups in circumstances where missions are constantly being explored. In our method, a group formation strategy that combines heuristic rules and response threshold models is proposed to dynamically adjust the members of the mission group and adapt to the needs of new missions. The degree of matching between the mission requirements and the group's capabilities, and the communication cost of group formation are used as indicators to evaluate the quality of the group. The response threshold method and the ant colony algorithm are selected as the comparison algorithms in the simulations. The results show that the grouping scheme obtained by the proposed method is superior to those of the comparison methods.


陈晨1,吴啸尘1,陈杰1,2,Panos M. PARDALOS3,丁舒忻4


Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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