Doxastic logic based on causal structures.

Belief revision and causality play an important role in many applications, typically, in the study of database update mechanisms and data dependence. New contributions on causal reasoning are continuously added to the pioneering works by Pearl, Halpern and others. Though there is a long tradition of...

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Publicado en:Synthese Vol. 205; no. 3; pp. 1 - 33
Autores principales: Xie, Kaibo, He, Qingyu
Formato: Artículo
Publicado: Springer Nature Mar2025
Acceso en línea:Ver este registro en EBSCOhost
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        10.1007/s11229-025-04946-3
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          Xie, Kaibo
          He, Qingyu
        affil:
          https://ror.org/033vjfk17 School of Philosophy, Wuhan University, Wuhan, China
          https://ror.org/03cve4549 Department of Philosophy, Tsinghua University, Beijing, China
      sug:
      keyword:
        Causal model
        Causal reasoning
        Conditional doxastic logic
        D-separation
        Philosophy and Religious Studies Philosophy
        Plausibility model
      ab: Belief revision and causality play an important role in many applications, typically, in the study of database update mechanisms and data dependence. New contributions on causal reasoning are continuously added to the pioneering works by Pearl, Halpern and others. Though there is a long tradition of modeling belief revision in philosophical logic, the entanglement between belief revision and causal reasoning has not yet been fully studied from a logical view. In this paper, we propose a new formal logic for doxastic causal reasoning. With examples, we illustrate that our framework explains rational belief revision based on causal reasoning. We also show that our framework can be used to account for conditionals in many examples which are problematic for the traditional causal modelling approach. We further study the general properties of the logic and its relations with causal Bayesian networks. A complete axiomatization, as well as a decidability result, will be given. In addition, we believe our work will shed light on understanding the relation between qualitative and quantitative approaches toward (causal) dependence in general.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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