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SCoCaT: Success Conditioned Constrained Reinforcement Learning for Spacecraft Docking
Termination-based constrained reinforcement learning is attractive for safety-critical robotic deployments: it avoids online optimization at inference, scales easily to many constraints via a single scalar per constraint, and is simpler to implement than commonly used Lagrangian methods. Instead of
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