On probability-raising causality in Markov decision processes

Christel BaierChristel Baier, Florian FunkeFlorian Funke, Jakob PiribauerJakob Piribauer, Robin ZiemekRobin Ziemek

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Christel Baier, Florian Funke, Jakob Piribauer, Robin Ziemek
On probability-raising causality in Markov decision processes
In Bouyer, Patricia and Schröder, Lutz, eds., Foundations of Software Science and Computation Structures, 40--60, 2022. Springer International Publishing

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KurzfassungAbstract
The purpose of this paper is to introduce a notion of causality in Markov decision processes based on the probability-raising principle and to analyze its algorithmic properties. The latter includes algorithms for checking causeeffect relationships and the existence of probability-raising causes for given effect scenarios. Inspired by concepts of statistical analysis, we study quality measures (recall, coverage ratio and f-score) for causes and develop algorithms for their computation. Finally, the computational complexity for finding optimal causes with respect to these measures is analyzed.
Forschungsgruppe:Research Group: Verifikation und formale quantitative Analyse„Verifikation und formale quantitative Analyse“ befindet sich nicht in der Liste (Computational Logic, Automatentheorie, Wissensverarbeitung, Knowledge-Based Systems, Knowledge Systems, Wissensbasierte Systeme, Logische Programmierung und Argumentation, Algebra und Diskrete Strukturen, Knowledge-aware Artificial Intelligence, Algebraische und logische Grundlagen der Informatik) zulässiger Werte für das Attribut „Forschungsgruppe“.Algebraic and Logical Foundations of Computer Science

@inproceedings{BFPZ2022,
  author    = {Christel Baier and Florian Funke and Jakob Piribauer and Robin
               Ziemek},
  title     = {On probability-raising causality in Markov decision processes},
  editor    = {Bouyer and Patricia and Schr{\"{o}}der and Lutz},
  booktitle = {Foundations of Software Science and Computation Structures},
  publisher = {Springer International Publishing},
  year      = {2022},
  pages     = {40--60},
  doi       = {10.1007/978-3-030-99253-8_3}
}