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...

Full description

Saved in:
Bibliographic Details
Published in:Chinese Control and Decision Conference pp. 1415 - 1420
Main Authors: An, Ruiqi, Li, Le, Bai, Miao, Zhang, Pu, Guo, Zhaozhi, Zuo, Ri
Format: Conference Proceeding
Language:English
Published: IEEE 16.05.2025
Subjects:
Autonomous underwater vehicles
AUV swarm
confrontation search
Decision making
multi-agent deep deterministic policy gradient algorithm
Search problems
Sonar detection
ISSN:1948-9447
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:1948-9447
DOI:10.1109/CCDC65474.2025.11090846