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Principled reward shaping for reinforcement learning via lyapunov stability theory

Neurocomputing, 2020
Abstract Reinforcement learning (RL) suffers from the designation in reward function and the large computational iterating steps until convergence. How to accelerate the training process in RL plays a vital role. In this paper, we proposed a Lyapunov function based approach to shape the reward function which can effectively accelerate the training ...
Yunlong Dong   +2 more
openaire   +3 more sources

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