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This groundbreaking research recently published in Science Robotics explores the use of reinforcement learning to optimize the trajectory of underwater robots. This AI methodology teaches robots how to optimize their actions in real-time to achieve specific objectives, even outperforming traditional methods. The research could pave the way for a more detailed understanding of marine ecological phenomena, such as the migration or movement patterns of various marine species, as well as real-time monitoring of other oceanographic instruments via a network of autonomous robots.
