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On-line Access: 2022-01-24

Received: 2020-07-17

Revision Accepted: 2022-04-22

Crosschecked: 2020-11-16

Cited: 0

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Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Chen CHEN

https://orcid.org/0000-0001-9354-6974

Xiaochen WU

https://orcid.org/0000-0002-9871-5543

Panos M. PARDALOS

https://orcid.org/0000-0001-9623-8053

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

http://doi.org/10.1631/FITEE.2000352


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",
volume="23",
number="1",
pages="86-100",
year="2022",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2000352"
}

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%T Dynamic grouping of heterogeneous agents for exploration and strike missions
%A Chen CHEN
%A Xiaochen WU
%A Jie CHEN
%A Panos M. PARDALOS
%A Shuxin DING
%J Frontiers of Information Technology & Electronic Engineering
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%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2000352

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T1 - Dynamic grouping of heterogeneous agents for exploration and strike missions
A1 - Chen CHEN
A1 - Xiaochen WU
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A1 - Shuxin DING
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VL - 23
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.2000352


Abstract: 
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.

探索与打击任务中异构智能体动态分组策略

陈晨1,吴啸尘1,陈杰1,2,Panos M. PARDALOS3,丁舒忻4
1北京理工大学自动化学院,中国北京市,100081
2同济大学控制科学与工程系,中国上海市,200092
3佛罗里达大学工业与系统工程系应用优化中心,美国佛罗里达州盖恩斯维尔市,32611
4中国铁道科学研究院集团有限公司通信信号研究所,中国北京市,100081
摘要:多变的环境和复杂的作战任务对无人作战智能体任务群组的构建提出了新的要求。本文旨在解决新需求下的任务群组动态构建问题。针对智能体的异构性,在不断探索任务的情况下群体形成方法需满足能动态形成新的群组。提出一种融合了启发式规则和响应阈值模型的群组形成策略,用于动态调整任务群组的成员以适应新的任务需求。将任务需求与群组能力的匹配程度以及群组的组网开销作为评价团队素质的指标。选取响应阈值法和蚁群算法作为仿真实验中的对比算法。结果表明所提方法在解决动态任务组形成问题时具备一定优势。

关键词:多智能体;动态作战任务;任务组形成;启发式规则;组网开销

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