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We distinguish two sub-types of each of the two causality principles formulated in connection with the Common Cause Principle in [Hen05] and raise and investigate the problem of logical relations among the resulting four causality…

Quantum Physics · Physics 2012-04-20 Miklós Rédei , Iñaki San Pedro

In this position paper we discuss three main shortcomings of existing approaches to counterfactual causality from the computer science perspective, and sketch lines of work to try and overcome these issues: (1) causality definitions should…

Logic in Computer Science · Computer Science 2017-10-11 Gregor Gössler , Oleg Sokolsky , Jean-Bernard Stefani

The principle of common cause is discussed as a possible fundamental principle of physics. Some revisions of Reichenbach's formulation of the principle are given, which lead to a version given by Bell. Various similar forms are compared and…

Quantum Physics · Physics 2007-05-23 Joe Henson

We propose a new definition of actual causes, using structural equations to model counterfactuals.We show that the definitions yield a plausible and elegant account ofcausation that handles well examples which have caused problems forother…

Artificial Intelligence · Computer Science 2013-01-14 Joseph Y. Halpern , Judea Pearl

In a recent article entitled "A simple explanation of the quantum violation of a fundamental inequality," Cabello proposes a condition on a class of probabilistic models that, he claims, gives the same bound on contextuality for the KCBS…

Quantum Physics · Physics 2012-10-25 Joe Henson

A fundamental question in causal inference is whether it is possible to reliably infer manipulation effects from observational data. There are a variety of senses of asymptotic reliability in the statistical literature, among which the most…

Artificial Intelligence · Computer Science 2012-12-12 Jiji Zhang , Peter L. Spirtes

At the heart of causal structure learning from observational data lies a deceivingly simple question: given two statistically dependent random variables, which one has a causal effect on the other? This is impossible to answer using…

Machine Learning · Computer Science 2020-10-13 Nikolaos Nikolaou , Konstantinos Sechidis

Given two time series, can one tell, in a rigorous and quantitative way, the cause and effect between them? Based on a recently rigorized physical notion namely information flow, we arrive at a concise formula and give this challenging…

Methodology · Statistics 2014-03-27 X. San Liang

Halpern and Pearl introduced a definition of actual causality; Eiter and Lukasiewicz showed that computing whether X=x is a cause of Y=y is NP-complete in binary models (where all variables can take on only two values) and\…

Artificial Intelligence · Computer Science 2014-12-10 Gadi Aleksandrowicz , Hana Chockler , Joseph Y. Halpern , Alexander Ivrii

Interactions between internet users are mediated by their devices and the common support infrastructure in data centres. Keeping track of causality amongst actions that take place in this distributed system is key to provide a seamless…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-08-12 Seyed Hossein Haeri , Peter Van Roy , Carlos Baquero , Christopher Meiklejohn

A serious defect with the Halpern-Pearl (HP) definition of causality is repaired by combining a theory of causality with a theory of defaults. In addition, it is shown that (despite a claim to the contrary) a cause according to the HP…

Artificial Intelligence · Computer Science 2008-12-18 Joseph Y. Halpern

We propose a new definition of actual cause, using structural equations to model counterfactuals. We show that the definition yields a plausible and elegant account of causation that handles well examples which have caused problems for…

Artificial Intelligence · Computer Science 2007-05-23 Joseph Y. Halpern , Judea Pearl

Perhaps the most prominent current definition of (actual) causality is due to Halpern and Pearl. It is defined using causal models (also known as structural equations models). We abstract the definition, extracting its key features, so that…

Artificial Intelligence · Computer Science 2025-11-27 Joseph Y. Halpern , Rafael Pass

The original Halpern-Pearl definition of causality [Halpern and Pearl, 2001] was updated in the journal version of the paper [Halpern and Pearl, 2005] to deal with some problems pointed out by Hopkins and Pearl [2003]. Here the definition…

Artificial Intelligence · Computer Science 2015-05-04 Joseph Y. Halpern

We present a definition of cause and effect in terms of decision-theoretic primitives and thereby provide a principled foundation for causal reasoning. Our definition departs from the traditional view of causation in that causal assertions…

Artificial Intelligence · Computer Science 2014-11-17 D. Heckerman , R. Shachter

Defeasibility in causal reasoning implies that the causal relationship between cause and effect can be strengthened or weakened. Namely, the causal strength between cause and effect should increase or decrease with the incorporation of…

Computation and Language · Computer Science 2024-06-28 Shaobo Cui , Lazar Milikic , Yiyang Feng , Mete Ismayilzada , Debjit Paul , Antoine Bosselut , Boi Faltings

The theory of actual causality, defined by Halpern and Pearl, and its quantitative measure - the degree of responsibility - was shown to be extremely useful in various areas of computer science due to a good match between the results it…

Software Engineering · Computer Science 2016-08-30 Hana Chockler

Causal models defined in terms of structural equations have proved to be quite a powerful way of representing knowledge regarding causality. However, a number of authors have given examples that seem to show that the Halpern-Pearl (HP)…

Artificial Intelligence · Computer Science 2019-02-20 Joseph Y. Halpern

Our article described an experiment that adjudicates between different causal accounts of Bell inequality violations by a comparison of their predictive power, finding that certain types of models that are structurally radical but…

Quantum Physics · Physics 2024-12-05 Patrick Daley , Kevin J. Resch , Robert W. Spekkens

Certain approaches to quantum gravity, such as the one based on the concept of purely virtual particles (fakeons), sacrifice the cause-effect relation at very small scales to reconcile renormalizability with unitarity. Other developments…

General Relativity and Quantum Cosmology · Physics 2026-05-01 Damiano Anselmi
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