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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

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

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

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

Since Pearl's seminal work on providing a formal language for causality, the subject has garnered a lot of interest among philosophers and researchers in artificial intelligence alike. One of the most debated topics in this context regards…

Artificial Intelligence · Computer Science 2015-10-30 Sander Beckers , Joost Vennekens

In previous work with Joost Vennekens I proposed a definition of actual causation that is based on certain plausible principles, thereby allowing the debate on causation to shift away from its heavy focus on examples towards a more…

Artificial Intelligence · Computer Science 2020-12-17 Sander Beckers

This paper deals with the problem of estimating the probability that one event was a cause of another in a given scenario. Using structural-semantical definitions of the probabilities of necessary or sufficient causation (or both), we show…

Artificial Intelligence · Computer Science 2013-01-18 Jin Tian , Judea Pearl

Reasoning about actual causes of observed effects is fundamental to the study of rationality. This important problem has been studied since the time of Aristotle, with formal mathematical accounts emerging recently. We live in a world where…

Artificial Intelligence · Computer Science 2026-02-17 Shakil M. Khan , Asim Mehmood , Sandra Zilles

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

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

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

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

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 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 (Beckers, 2025) I introduced nondeterministic causal models as a generalization of Pearl's standard deterministic causal models. I here take advantage of the increased expressivity offered by these models to offer a novel definition of…

Artificial Intelligence · Computer Science 2025-03-12 Sander Beckers

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

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

Causality is typically treated an all-or-nothing concept; either A is a cause of B or it is not. We extend the definition of causality introduced by Halpern and Pearl [2001] to take into account the degree of responsibility of A for B. For…

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

Causal reasoning is essential for understanding decision-making about the behaviour of complex `ecosystems' of systems that underpin modern society, with security -- including issues around correctness, safety, resilience, etc. -- typically…

Logic in Computer Science · Computer Science 2025-08-05 Pinaki Chakraborty , Tristan Caulfield , David Pym
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