水下无人系统学报2024，Vol.32Issue(1)：79-86,8.DOI:10.11993/j.issn.2096-3920.2023-0159
基于多智能体深度强化学习的无人艇集群博弈对抗研究
Research on Game Confrontation of Unmanned Surface Vehicles Swarm Based on Multi-Agent Deep Reinforcement Learning
摘要
Abstract
Based on the background of future modern maritime combats,a multi-agent deep reinforcement learning scheme was proposed to complete the cooperative round-up task in the swarm game confrontation of unmanned surface vehicles(USVs).First,based on different combat modes and application scenarios,a multi-agent deep deterministic policy gradient algorithm based on distributed execution was determined,and its principle was introduced.Second,specific combat scenario platforms were simulated,and multi-agent network models,reward function mechanisms,and training strategies were designed.The experimental results show that the method proposed in this article can effectively solve the problem of cooperative round-up decision-making facing USVs from the enemy,and it has high efficiency in different combat scenarios.This work provides theoretical and reference value for the research on intelligent decision-making of USVs in complicated combat scenarios in the future.关键词
无人艇集群/多智能体深度确定性策略梯度算法/深度强化学习/智能决策/博弈对抗Key words
unmanned surface vehicle swarm/multi-agent deep deterministic policy gradient algorithm/deep reinforcement learning/intelligent decision-making/game confrontation分类
军事科技引用本文复制引用
于长东,刘新阳,陈聪,刘殿勇,梁霄..基于多智能体深度强化学习的无人艇集群博弈对抗研究[J].水下无人系统学报,2024,32(1):79-86,8.基金项目
国家自然科学基金项目(52271302) （52271302）
国家基础科研计划项目(JCKY2022410C012) （JCKY2022410C012）
辽宁省应用基础研究计划项目(2023JH2/101300198) （2023JH2/101300198）
大连市科技创新基金项目(2021JJ12GX017) （2021JJ12GX017）
中央高校基本科研业务费专项资金资助(3132023512) （3132023512）
智能海洋航行器技术全国重点实验室支持项目(2024-HYHXQ-WDZC08). （2024-HYHXQ-WDZC08）
