Nicolas Markey

Abstract

In this paper, we are interested in the synthesis of schedulers in double-weighted Markov decision processes, which satisfy both a percentile constraint over a weighted reachability condition, and a quantitative constraint on the expected value of a random variable defined using a weighted reachability condition. This problem is inspired by the modelization of an electric-vehicle charging problem. We study the cartography of the problem, when one parameter varies, and show how a partial cartography can be obtained via two sequences of opimization problems. We discuss completeness and feasability of the method.

@inproceedings{gandalf2018-BGMR,
  author =              {Bouyer, Patricia and Gonz{\'a}lez, Mauricio and
                         Markey, Nicolas and Randour, Mickael},
  title =               {Multi-weighted Markov Decision Processes with
                         Reachability Objectives},
  editor =              {Orlandini, Andrea and Zimmermann, Martin},
  booktitle =           {{P}roceedings of the 9th {I}nternational {S}ymposium
                         on {G}ames, {A}utomata, {L}ogics and {F}ormal
                         {V}erification ({GandALF}'18)},
  acronym =             {{GandALF}'18},
  series =              {Electronic Proceedings in Theoretical Computer
                         Science},
  volume =              {277},
  pages =               {250-264},
  year =                {2018},
  month =               sep,
  doi =                 {10.4204/EPTCS.277.18},
  abstract =            {In~this paper, we~are interested in the synthesis of
                         schedulers in double-weighted Markov decision
                         processes, which satisfy both a percentile
                         constraint over a weighted reachability condition,
                         and a quantitative constraint on the expected value
                         of a random variable defined using a weighted
                         reachability condition. This~problem is inspired by
                         the modelization of an electric-vehicle charging
                         problem. We study the cartography of the problem,
                         when one parameter varies, and show how a partial
                         cartography can be obtained via two sequences of
                         opimization problems. We~discuss completeness and
                         feasability of the method.},
}