Multi-weighted Markov Decision Processes with Reachability Objectives

Patricia Bouyer
Mauricio González
Nicolas Markey
Mickael Randour

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.

In Andrea Orlandini and Martin Zimmermann: Proceedings Ninth International Symposium on Games, Automata, Logics, and Formal Verification (GandALF 2018), Saarbrücken, Germany, 26-28th September 2018, Electronic Proceedings in Theoretical Computer Science 277, pp. 250–264.
Published: 7th September 2018.

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