水下无人系统学报2026，Vol.34Issue(4)：726-740,15.DOI:10.11993/j.issn.2096-3920.2025-0173
基于延迟鲁棒多智能体强化学习的协同围捕方法
A Cooperative Encirclement Method Based on Delay-Robust Multi-Agent Reinforcement Learning
付松琛 1白乐天 1赵少靖 1蒙傲萌 1梁宏 1黎塔1
作者信息
- 1. 中国科学院声学研究所 语音与智能信息处理实验室,北京,100190||中国科学院大学,北京,100049
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摘要
Abstract
To address delayed observations caused by acoustic communication in cooperative operations of multiple unmanned undersea vehicles(UUVs),a cooperative encirclement method based on delay-robust multi-agent reinforcement learning was proposed.First,the mechanism of delayed observations was analyzed under common communication scenarios.Second,a turbulent flow field was modeled using the two-dimensional Navier-Stokes equations to construct a simulation environment that reflects realistic task settings.Then,a delay-robust multi-agent reinforcement learning method was proposed,and its constituent modules were described in detail.On this basis,the reward functions for the encirclement task,the network architectures,and the training procedures were designed,and ablation studies were conducted under different tasks and delay conditions.Experimental results demonstrate that the proposed method effectively handles delayed observations and maintains strong performance under varying delay levels,approaching the theoretical upper bound of the no-delay case in some tasks.Furthermore,the ablation results verify the effectiveness of each module in mitigating delayed observations,providing new theoretical support and a practical methodology for multi-UUV cooperative strategies under delayed observations.关键词
无人水下航行器/协同围捕/多智能体强化学习/延迟观测Key words
unmanned undersea vehicle/cooperative encirclement/multi-agent reinforcement learning/delayed observation分类
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付松琛,白乐天,赵少靖,蒙傲萌,梁宏,黎塔..基于延迟鲁棒多智能体强化学习的协同围捕方法[J].水下无人系统学报,2026,34(4):726-740,15.
