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English(EN) Task-Oriented Sensing and Covert Transmissions for Collaborative Multi-AUV Systems

新的MARL框架增强了隐蔽约束下的AUV协作

作者 PulseAugur 编辑部 · [3 个来源] ·

本文介绍了感知信息价值实现多智能体强化学习（SVR-MARL）框架，该框架专为多自主水下航行器（AUV）的协作任务设计。该框架解决了水下环境中感知能力有限和通信风险的挑战，因为主动感知和声学通信会增加暴露的风险。SVR-MARL旨在通过学习考虑实际通信约束和感知信息效用的分布式策略来优化协作任务效率，并在协作定位和跟踪的案例研究中进行了演示。 AI

影响 这项研究可以提高自主水下航行器协同操作的效率和隐蔽性。

排序理由 该集群包含一篇详细介绍多智能体强化学习新框架的研究论文。

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 3 个来源。 我们如何撰写摘要 →

新的MARL框架增强了隐蔽约束下的AUV协作

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报道来源 [3]

  1. arXiv cs.LG TIER_1 English(EN) · Xueyao Zhang, Chenyang Yan, Bo Yang, Xuelin Cao, Zhiwen Yu, Bin Guo, George C. Alexandropoulos, Merouane Debbah, Chau Yuen ·

    面向协作式多AUV系统的面向任务感知与隐蔽传输

    arXiv:2607.13880v1 Announce Type: new Abstract: In underwater covert cooperative missions, autonomous underwater vehicles (AUVs) often cannot rely on active sonar to continuously obtain complete information, since active sensing and frequent communications increase the risk of ex…

  2. arXiv cs.LG TIER_1 English(EN) · Chau Yuen ·

    面向协作式多AUV系统的面向任务感知与隐蔽传输

    In underwater covert cooperative missions, autonomous underwater vehicles (AUVs) often cannot rely on active sonar to continuously obtain complete information, since active sensing and frequent communications increase the risk of exposure. As a result, AUVs primarily rely on pass…

  3. Hugging Face Daily Papers TIER_1 English(EN) ·

    面向任务的感知与隐蔽通信用于协同多AUV系统

    In underwater covert cooperative missions, autonomous underwater vehicles (AUVs) often cannot rely on active sonar to continuously obtain complete information, since active sensing and frequent communications increase the risk of exposure. As a result, AUVs primarily rely on pass…

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