Causal Kripke models

Abstract In causal reasoning literature, the term actual causality is used to refer to the causality of some specific event that actually happened. One of the most prominent approaches for reasoning about actual causality is that of causal models developed by Halpern and Pearl (Pearl, Causality 2009, Halpern, British Journal for the Philosophy of Science 2005, Halpern, British Journal for the Philosophy of Science 2005). In this work, we extend Halpern and Pearl’s models for actual causality to an environment of possible world semantics. In this environment, we introduce a logic of actual causality with modal operators and provide sound and (weakly) complete axiomatization for this logic. This logic can be used for reasoning about causality in scenarios involving multiple possibilities, uncertainty and knowledge. Based on this new framework, we define what it means for an agent’s knowledge or lack of knowledge of some event to be an actual cause of some other event. We provide several examples to illustrate that our framework and definitions provide an intuitive environment to reason about actual causality in these scenarios.

Authors

Institutions

Publication Details

Journal
Synthese
Published
2025-08-29
DOI
https://doi.org/10.1007/s11229-025-05223-z
Primary Topic
Bayesian Modeling and Causal Inference
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Causal Kripke models

Apostolos Tzimoulis, Krishna Manoorkar, Xiaolong Wang, Ruoding Wang et al.
Synthese
Bayesian Modeling and Causal Inference
article

Causal Kripke models

Apostolos Tzimoulis, Krishna Manoorkar, Xiaolong Wang, Ruoding Wang, Y. J. Ding
article en

Abstract

Abstract In causal reasoning literature, the term actual causality is used to refer to the causality of some specific event that actually happened. One of the most prominent approaches for reasoning about actual causality is that of causal models developed by Halpern and Pearl (Pearl, Causality 2009, Halpern, British Journal for the Philosophy of Science 2005, Halpern, British Journal for the Philosophy of Science 2005). In this work, we extend Halpern and Pearl’s models for actual causality to an environment of possible world semantics. In this environment, we introduce a logic of actual causality with modal operators and provide sound and (weakly) complete axiomatization for this logic. This logic can be used for reasoning about causality in scenarios involving multiple possibilities, uncertainty and knowledge. Based on this new framework, we define what it means for an agent’s knowledge or lack of knowledge of some event to be an actual cause of some other event. We provide several examples to illustrate that our framework and definitions provide an intuitive environment to reason about actual causality in these scenarios.

SyntheseVol. 206(3)
Shandong University (CN), Xiamen University (CN), Vrije Universiteit Amsterdam (NL)
Openalex Percentile: Top 88%
Bayesian Modeling and Causal Inference
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.