Characterizing Markov Decision Processes

@inproceedings{Ratitch2002CharacterizingMD,
  title={Characterizing Markov Decision Processes},
  author={Bohdana Ratitch and Doina Precup},
  booktitle={ECML},
  year={2002}
}
Problem characteristics often have a significant influence on the difficulty of solving optimization problems. In this paper, we propose attributes for characterizing Markov Decision Processes (MDPs), and discuss how they affect the performance of reinforcement learning algorithms that use function approximation. The attributes measure mainly the amount of randomness in the environment. Their values can be calculated from the MDP model or estimated on-line. We show empirically that two of the… CONTINUE READING
Highly Cited
This paper has 18 citations. REVIEW CITATIONS

References

Publications referenced by this paper.

Similar Papers

Loading similar papers…