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Toward Computationally Efficient Inverse Reinforcement Learning via Reward Shaping
Inverse reinforcement learning (IRL) is computationally challenging, with common approaches requiring the solution of multiple …
Lauren H. Cooke*, Harvey Klyne*, Edwin Zhang*, Cassidy Laidlaw, Milind Tambe, Finale Doshi-Velez
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Toward Computationally Efficient Inverse Reinforcement Learning via Reward Shaping