APRIL: Active Preference-learning based Reinforcement Learning

  title={APRIL: Active Preference-learning based Reinforcement Learning},
  author={Riad Akrour and Marc Schoenauer and Mich{\`e}le Sebag},
This paper focuses on reinforcement learning (RL) with limited prior knowledge. In the domain of swarm robotics for instance, the expert can hardly design a reward function or demonstrate the target behavior, forbidding the use of both standard RL and inverse reinforcement learning. Although with a limited expertise, the human expert is still often able to emit preferences and rank the agent demonstrations. Earlier work has presented an iterative preference-based RL framework: expert… CONTINUE READING
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