A fast hybrid reinforcement learning framework with human corrective feedback
نویسندگان
چکیده
منابع مشابه
Reinforcement learning with human feedback
As computational agents are increasingly used beyond research labs, their success will depend on their ability to learn new skills and adapt to their dynamic, complex environments. If human users — without programming skills — can transfer their task knowledge to the agents, learning rates can increase dramatically, reducing costly trials. The TAMER framework guides the design of agents whose b...
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ژورنال
عنوان ژورنال: Autonomous Robots
سال: 2018
ISSN: 0929-5593,1573-7527
DOI: 10.1007/s10514-018-9786-6