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An Inferential Theory of Causal Reasoning

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Logic, Rationality, and Interaction (LORI 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14329))

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Abstract

We present a general formalism of causal reasoning that encompasses both Pearl’s approach to causality and a number of key systems of nonmonotonic reasoning in artificial intelligence.

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Notes

  1. 1.

    We assume that the labels of associated propositions are self-explanatory.

  2. 2.

    See [20] for a similar point.

  3. 3.

    In what follows, causal rules \(a\Rightarrow A\) are used both as formal objects of our theory and as statements in the meta-language (saying that a causes A).

  4. 4.

    For instance, A can directly cause B, though there are no intermediate causes between A and B.

  5. 5.

    Here \(C_{\varDelta }\) is a causal operator corresponding to the least supraclassical causal inference relation containing \(\varDelta \).

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Author information

Authors and Affiliations

  1. School of Computer Science, Holon Institute of Technology (HIT), Holon, Israel

    Alexander Bochman

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  1. Alexander Bochman
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Correspondence to Alexander Bochman .

Editor information

Editors and Affiliations

  1. Utrecht University, Utrecht, The Netherlands

    Natasha Alechina

  2. CNRS, IRIT, Toulouse, France

    Andreas Herzig

  3. Shandong University, Jinan, China

    Fei Liang

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Bochman, A. (2023). An Inferential Theory of Causal Reasoning. In: Alechina, N., Herzig, A., Liang, F. (eds) Logic, Rationality, and Interaction. LORI 2023. Lecture Notes in Computer Science, vol 14329. Springer, Cham. https://doi.org/10.1007/978-3-031-45558-2_1

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  • DOI: https://doi.org/10.1007/978-3-031-45558-2_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-45557-5

  • Online ISBN: 978-3-031-45558-2

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