Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning

ArXi:2510.03534v5 Announce Type: replace-cross We study the problem of long-term (multiple days) mapping of a river plume using multiple autonomous underwater vehicles (AUVs), focusing on the Douro river representative use-case. We propose an energy - and communication - efficient multi-agent reinforcement learning approach in which a central coordinator intermittently communicates with the AUVs, collecting measurements and issuing commands.