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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

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

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

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 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

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

Causality is the relationship where one event contributes to the production of another, with the cause being partly responsible for the effect and the effect partly dependent on the cause. In this paper, we propose a novel and effective…

Logic in Computer Science · Computer Science 2024-09-04 Arshia Rafieioskouei , Borzoo Bonakdarpour

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

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

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

Detecting and understanding reasons for defects and inadvertent behavior in software is challenging due to their increasing complexity. In configurable software systems, the combinatorics that arises from the multitude of features a user…

Software Engineering · Computer Science 2022-03-01 Clemens Dubslaff , Kallistos Weis , Christel Baier , Sven Apel

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 study formal languages which are capable of fully expressing quantitative probabilistic reasoning and do-calculus reasoning for causal effects, from a computational complexity perspective. We focus on satisfiability problems whose…

Artificial Intelligence · Computer Science 2023-05-17 Benito van der Zander , Markus Bläser , Maciej Liśkiewicz

The notion of actual causation, as formalized by Halpern and Pearl, has been recently applied to relational databases, to characterize and compute actual causes for possibly unexpected answers to monotone queries. Causes take the form of…

Databases · Computer Science 2016-04-26 Babak Salimi , Leopoldo Bertossi , Dan Suciu , Guy Van den Broeck

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

Many objectives can be achieved (or may be achieved more effectively) only by a group of agents executing a team plan. If a team plan fails, it is often of interest to determine what caused the failure, the degree of responsibility of each…

Artificial Intelligence · Computer Science 2020-05-22 Natasha Alechina , Joseph Y. Halpern , Brian Logan

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

Actual causality is increasingly well understood. Recent formal approaches, proposed by Halpern and Pearl, have made this concept mature enough to be amenable to automated reasoning. Actual causality is especially vital for building…

Artificial Intelligence · Computer Science 2020-10-16 Amjad Ibrahim , Alexander Pretschner

The framework of Pearl's Causal Hierarchy (PCH) formalizes three types of reasoning: probabilistic (i.e. purely observational), interventional, and counterfactual, that reflect the progressive sophistication of human thought regarding…

Artificial Intelligence · Computer Science 2025-02-07 Julian Dörfler , Benito van der Zander , Markus Bläser , Maciej Liskiewicz

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
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