AUV Swarm Confrontation Search Method Based on the MADDPG Algorithm
In this paper, an Autonomous Underwater Vehicle (AUV) swarm confrontation search method based on the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm is proposed for the AUV swarm confrontation search problem. Firstly, the AUV swarm confrontation search model is constructed. Secondl...
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| Veröffentlicht in: | Chinese Control and Decision Conference S. 1415 - 1420 |
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| Hauptverfasser: | , , , , , |
| Format: | Tagungsbericht |
| Sprache: | Englisch |
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IEEE
16.05.2025
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| ISSN: | 1948-9447 |
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| Abstract | In this paper, an Autonomous Underwater Vehicle (AUV) swarm confrontation search method based on the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm is proposed for the AUV swarm confrontation search problem. Firstly, the AUV swarm confrontation search model is constructed. Secondly, the multiagent state space, action space, observation space, and reward function are designed for the AUV swarm confrontation search problem, and the MADDPG algorithm is adopted to obtain the AUV swarm confrontation search method. Finally, the effectiveness and the generality of the proposed AUV swarm confrontation search method are verified by simulation experiments for the AUV swarm confrontation search tasks under different speed conditions and sonar detection distances. |
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| AbstractList | In this paper, an Autonomous Underwater Vehicle (AUV) swarm confrontation search method based on the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm is proposed for the AUV swarm confrontation search problem. Firstly, the AUV swarm confrontation search model is constructed. Secondly, the multiagent state space, action space, observation space, and reward function are designed for the AUV swarm confrontation search problem, and the MADDPG algorithm is adopted to obtain the AUV swarm confrontation search method. Finally, the effectiveness and the generality of the proposed AUV swarm confrontation search method are verified by simulation experiments for the AUV swarm confrontation search tasks under different speed conditions and sonar detection distances. |
| Author | Bai, Miao An, Ruiqi Guo, Zhaozhi Li, Le Zuo, Ri Zhang, Pu |
| Author_xml | – sequence: 1 givenname: Ruiqi surname: An fullname: An, Ruiqi email: arq@mail.nwpu.edu.cn organization: School of Marine Science and Technology, Northwestern Polytechnical University,Xi'an,China – sequence: 2 givenname: Le surname: Li fullname: Li, Le email: leli@nwpu.edu.cn organization: School of Marine Science and Technology, Northwestern Polytechnical University,Xi'an,China – sequence: 3 givenname: Miao surname: Bai fullname: Bai, Miao email: 1959289732@qq.com organization: National Elite Institute of Engineering, Northwestern Polytechnical University,Xi'an,China – sequence: 4 givenname: Pu surname: Zhang fullname: Zhang, Pu email: 2085208482@qq.com organization: National Elite Institute of Engineering, Northwestern Polytechnical University,Xi'an,China – sequence: 5 givenname: Zhaozhi surname: Guo fullname: Guo, Zhaozhi email: rangergzz@163.com organization: School of Marine Science and Technology, Northwestern Polytechnical University,Xi'an,China – sequence: 6 givenname: Ri surname: Zuo fullname: Zuo, Ri email: zuori@mail.nwpu.edu.cn organization: School of Marine Science and Technology, Northwestern Polytechnical University,Xi'an,China |
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| Snippet | In this paper, an Autonomous Underwater Vehicle (AUV) swarm confrontation search method based on the Multi-Agent Deep Deterministic Policy Gradient (MADDPG)... |
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| SubjectTerms | Autonomous underwater vehicles AUV swarm confrontation search Decision making multi-agent deep deterministic policy gradient algorithm Search problems Sonar detection |
| Title | AUV Swarm Confrontation Search Method Based on the MADDPG Algorithm |
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