An Automated Measure of MDP Similarity for Transfer in Reinforcement Learning

@inproceedings{Ammar2014AnAM,
  title={An Automated Measure of MDP Similarity for Transfer in Reinforcement Learning},
  author={Haitham Bou Ammar and Eric Eaton and Gerhard Weiss Kurt Driessens and Karl Tuyls and Decebal Mocanu Matthew Taylor},
  year={2014}
}
Transfer learning can improve the reinforcement learning of a new task by allowing the agent to reuse knowledge acquired from other source tasks. Despite their success, transfer learning methods rely on having relevant source tasks; transfer from inappropriate tasks can inhibit performance on the new task. For fully autonomous transfer, it is critical to have a method for automatically choosing relevant source tasks, which requires a similarity measure between Markov Decision Processes (MDPs… CONTINUE READING
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