• Computer Science
  • Published in ArXiv 2017

Agent-Agnostic Human-in-the-Loop Reinforcement Learning

@article{Abel2017AgentAgnosticHR,
  title={Agent-Agnostic Human-in-the-Loop Reinforcement Learning},
  author={David Abel and John Salvatier and Andreas Stuhlm{\"u}ller and Owain Evans},
  journal={ArXiv},
  year={2017},
  volume={abs/1701.04079}
}
Providing Reinforcement Learning agents with expert advice can dramatically improve various aspects of learning. Prior work has developed teaching protocols that enable agents to learn efficiently in complex environments; many of these methods tailor the teacher's guidance to agents with a particular representation or underlying learning scheme, offering effective but specialized teaching procedures. In this work, we explore protocol programs, an agent-agnostic schema for Human-in-the-Loop… CONTINUE READING
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