Incremental Methods for Computing Bounds in Partially Observable Markov Decision Processes

@inproceedings{Hauskrecht1997IncrementalMF,
  title={Incremental Methods for Computing Bounds in Partially Observable Markov Decision Processes},
  author={Milos Hauskrecht},
  booktitle={AAAI/IAAI},
  year={1997}
}
Partially observable Markov decision processes (POMDPs) allow one to model complex dynamic decision or control problems that include both action outcome uncertainty and imperfect observability. The control problem is formulated as a dynamic optimization problem with a value function combining costs or rewards from multiple steps. In this paper we propose, analyse and test various incremental methods for computing bounds on the value function for control problems with infinite discounted horizon… CONTINUE READING

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