On probability-raising causality in Markov decision processes

@inproceedings{Baier2022OnPC,
  title={On probability-raising causality in Markov decision processes},
  author={Christel Baier and Florian Funke and Jakob Piribauer and Robin Ziemek},
  booktitle={FoSSaCS},
  year={2022}
}
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… 
1 Citations

Foundations of probability-raising causality in Markov decision processes

The paper lays the mathematical foundations and analyzes the algorithmic properties of these cause-effect relations, which includes algorithms for checking cause conditions given an effect and deciding the existence of probability-raising causes.

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