Bayesian multitask inverse reinforcement learning

  title={Bayesian multitask inverse reinforcement learning},
  author={Christos Dimitrakakis and Constantin A. Rothkopf},
We generalise the problem of inverse reinforcement learning to multiple tasks, from multiple demonstrations. Each one may represent one expert trying to solve a different task, or as different experts trying to solve the same task. Our main contribution is to formalise the problem as statistical preference elicitation, via a number of structured priors, whose form captures our biases about the relatedness of different tasks or expert policies. In doing so, we introduce a prior on policy… CONTINUE READING
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