Corpus ID: 210164907

Point-Based Methods for Model Checking in Partially Observable Markov Decision Processes

@article{Bouton2020PointBasedMF,
  title={Point-Based Methods for Model Checking in Partially Observable Markov Decision Processes},
  author={Maxime Bouton and Jana Tumova and Mykel J. Kochenderfer},
  journal={ArXiv},
  year={2020},
  volume={abs/2001.03809}
}
  • Maxime Bouton, Jana Tumova, Mykel J. Kochenderfer
  • Published in AAAI 2020
  • Computer Science
  • ArXiv
  • Autonomous systems are often required to operate in partially observable environments. They must reliably execute a specified objective even with incomplete information about the state of the environment. We propose a methodology to synthesize policies that satisfy a linear temporal logic formula in a partially observable Markov decision process (POMDP). By formulating a planning problem, we show how to use point-based value iteration methods to efficiently approximate the maximum probability… CONTINUE READING

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