arXiv Machine Learning By Jiaao Ma, Chuan Lin, Guangjie Han, Shengchao Zhu, Zhenyu Wang, Chen An

Diffusion-Guided Cooperative Policy Learning for Target Tracking Based on Underwater Mobile Agent Networks

Read the original on arXiv Machine Learning →

arXiv:2603. 29426v2 Announce Type: replace-cross Abstract: Multi-agent reinforcement learning (MARL) provides a promising solution for cooperative target tracking in networks of autonomous underwater vehicles (AUVs).

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv Machine Learning
5d ago

Multi-AUV Ad-hoc network-based Target Tracking: A Value Gradient Guidance Multi-Agent Diffusion Reinforcement Learning Approach

arXiv:2608. 12436v1 Announce Type: new Abstract: Multi-AUV ad-hoc network-based target tracking requires networked autonomous underwater vehicles (AUVs) to cooperatively track maneuvering targets under constrained acoustic communication, dynamic topology, and uncertain ocean disturbances.

By Jiaao Ma, Chuan Lin, Guangjie Han, Shengchao Zhu, Qian Zhu, Ying Liu, Zhenyu Wang
arXiv AI
Jun 4

Contextual Multi-Task Reinforcement Learning for Autonomous Reef Monitoring

arXiv:2604. 12645v2 Announce Type: replace-cross Abstract: Although autonomous underwater vehicles promise the capability of marine ecosystem monitoring, their deployment is fundamentally limited by the difficulty of controlling vehicles under highly uncertain and non-stationary underwater dynamics.

By Melvin Laux, Yi-Ling Liu, Rina Alo, S\"oren T\"opper, Mariela De Lucas Alvarez, Frank Kirchner, Rebecca Adam