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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

Thinking in terms of causality helps us structure how different parts of a system depend on each other, and how interventions on one part of a system may result in changes to other parts. Therefore, formal models of causality are an…

Artificial Intelligence · Computer Science 2021-04-05 Matvey Soloviev , Joseph Y. Halpern

Pearl opened the door to formally defining actual causation using causal models. His approach rests on two strategies: first, capturing the widespread intuition that X=x causes Y=y iff X=x is a Necessary Element of a Sufficient Set for Y=y,…

Artificial Intelligence · Computer Science 2021-02-05 Sander Beckers

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

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

A definition of causality introduced by Halpern and Pearl, which uses structural equations, is reviewed. A more refined definition is then considered, which takes into account issues of normality and typicality, which are well known to…

Artificial Intelligence · Computer Science 2014-12-10 Joseph Y. Halpern

This work extends Halpern and Pearl's causal models for actual causality to a possible world semantics environment. Using this framework we introduce a logic of actual causality with modal operators, which allows for reasoning about…

Artificial Intelligence · Computer Science 2023-07-13 Yiwen Ding , Krishna Manoorkar , Apostolos Tzimoulis , Ruoding Wang , Xiaolong Wang

We show that it is possible to understand and identify a decision maker's subjective causal judgements by observing her preferences over interventions. Following Pearl [2000], we represent causality using causal models (also called…

Theoretical Economics · Economics 2024-01-23 Joseph Y. Halpern , Evan Piermont

One of the key challenges when looking for the causes of a complex event is to determine the causal status of factors that are neither individually necessary nor individually sufficient to produce that event. In order to reason about how…

Artificial Intelligence · Computer Science 2017-10-11 Sjur K Dyrkolbotn

Causal models have proven extremely useful in offering formal representations of causal relationships between a set of variables. Yet in many situations, there are non-causal relationships among variables. For example, we may want variables…

Artificial Intelligence · Computer Science 2023-01-18 Sander Beckers , Joseph Y. Halpern , Christopher Hitchcock

Causality has been the issue of philosophic debate since Hippocrates. It is used in formal verification and testing, e.g., to explain counterexamples or construct fault trees. Recent work defines actual causation in terms of Pearl's…

Logic in Computer Science · Computer Science 2019-11-01 Robert Künnemann , Deepak Garg , Michael Backes

This paper presents a sound and completecalculus for causal relevance, based onPearl's functional models semantics.The calculus consists of axioms and rulesof inference for reasoning about causalrelevance relationships.We extend the set of…

Artificial Intelligence · Computer Science 2013-01-14 Blai Bonet

In view of the growing complexity of modern software architectures, formal models are increasingly used to understand why a system works the way it does, opposed to simply verifying that it behaves as intended. This paper surveys approaches…

Logic in Computer Science · Computer Science 2021-05-21 Christel Baier , Clemens Dubslaff , Florian Funke , Simon Jantsch , Rupak Majumdar , Jakob Piribauer , Robin Ziemek

We look more carefully at the modeling of causality using structural equations. It is clear that the structural equations can have a major impact on the conclusions we draw about causality. In particular, the choice of variables and their…

Artificial Intelligence · Computer Science 2011-06-15 Joseph Y. Halpern , Christopher Hitchcock

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

Given a causal model of some domain and a particular story that has taken place in this domain, the problem of actual causation is deciding which of the possible causes for some effect actually caused it. One of the most influential…

Artificial Intelligence · Computer Science 2011-07-26 Joost Vennekens

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

In this paper, we continue our research on the algorithmic aspects of Halpern and Pearl's causes and explanations in the structural-model approach. To this end, we present new characterizations of weak causes for certain classes of causal…

Artificial Intelligence · Computer Science 2013-01-07 Thomas Eiter , Thomas Lukasiewicz

Causal models defined in terms of a collection of equations, as defined by Pearl, are axiomatized here. Axiomatizations are provided for three successively more general classes of causal models: (1) the class of recursive theories (those…

Artificial Intelligence · Computer Science 2014-08-08 Joseph Y. Halpern

Causal models defined in terms of a collection of equations, as defined by Pearl, are axiomatized here. Axiomatizations are provided for three successively more general classes of causal models: (1) the class of recursive theories (those…

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