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RAMP: Hybrid DRL for Online Learning of Numeric Action Models

ArXiv CS.AI13 Apr
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RAMP combines reinforcement learning, action model learning, and planning to enable online learning of numeric action models—eliminating the need for expert traces. This advance makes automated planning more practical for real-world applications where collecting offline expert data is expensive or infeasible, potentially accelerating deployment of autonomous systems.

New hybrid approach enables AI systems to learn action models while actively exploring environments.

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