Apprenticeship learning using linear programming

@inproceedings{Syed2008ApprenticeshipLU,
  title={Apprenticeship learning using linear programming},
  author={Umar Syed and Michael H. Bowling and Robert E. Schapire},
  booktitle={ICML},
  year={2008}
}
In apprenticeship learning, the goal is to learn a policy in a Markov decision process that is at least as good as a policy demonstrated by an expert. The difficulty arises in that the MDP's true reward function is assumed to be unknown. We show how to frame apprenticeship learning as a linear programming problem, and show that using an off-the-shelf LP solver to solve this problem results in a substantial improvement in running time over existing methods---up to two orders of magnitude faster… CONTINUE READING
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