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A team from Sorbonne University Abu Dhabi developed a new mechanism for underwater robot teams that learn to collaborate through reinforcement learning, with the aim of efficiently inspecting unknown pipes. The mechanism relies on simulating real-world conditions and utilizes an interpretable logical framework instead of neural networks, making the robots' policies easier to understand. The results showed that collective cooperation accelerates the learning process and improves coverage, especially in environments with poor visibility.
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