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arXiv · 1809.03107

Multi-weighted Markov Decision Processes with Reachability Objectives

Patricia Bouyer·Mauricio González·Nicolas Markey·Mickael Randour
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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.

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Patricia Bouyer, Mauricio González, Nicolas Markey, Mickael Randour. 2018-09-10. Multi-weighted Markov Decision Processes with Reachability Objectives. https://doi.org/10.4204/eptcs.277.18

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