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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

I propose the purpose our concept of actual causation serves is minimizing various cost in intervention practice. Actual causation has three features: nonredundant sufficiency, continuity and abnormality; these features correspond to the…

Artificial Intelligence · Computer Science 2017-08-01 Liang Zhou

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

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

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

Understanding the laws that govern a phenomenon is the core of scientific progress. This is especially true when the goal is to model the interplay between different aspects in a causal fashion. Indeed, causal inference itself is…

Artificial Intelligence · Computer Science 2025-08-27 Alessio Zanga , Elif Ozkirimli , Fabio Stella

We study the problem of deriving policies, or rules, that when enacted on a complex system, cause a desired outcome. Absent the ability to perform controlled experiments, such rules have to be inferred from past observations of the system's…

Machine Learning · Computer Science 2020-09-09 Kailash Budhathoki , Mario Boley , Jilles Vreeken

We propose new definitions of (causal) explanation, using structural equations to model counterfactuals. The definition is based on the notion of actual cause, as defined and motivated in a companion paper. Essentially, an explanation is a…

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

Inference about treatment effects for time-to-event outcomes is often obscured by the presence of competing events. A particularly complex situation arises when the treatment influences the occurrence of the competing event. A comprehensive…

Debugging is commonly understood as finding and fixing the cause of a problem. But what does ``cause'' mean? How can we find causes? How can we prove that a cause is a cause--or even ``the'' cause? This paper defines common terms in…

Software Engineering · Computer Science 2007-05-23 Andreas Zeller

Reasoning about observed effects and their causes is important in multi-agent contexts. While there has been much work on causality from an objective standpoint, causality from the point of view of some particular agent has received much…

Artificial Intelligence · Computer Science 2019-11-01 Shakil M. Khan , Mikhail Soutchanski

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

Machine learning is the science of discovering statistical dependencies in data, and the use of those dependencies to perform predictions. During the last decade, machine learning has made spectacular progress, surpassing human performance…

Machine Learning · Statistics 2016-07-13 David Lopez-Paz

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

Assembly theory (AT) introduces causation as a material property and establishes a metrology for objects produced by evolution and selection. The physical scale of causation is quantified by the assembly index, defined as the minimum number…

History and Philosophy of Physics · Physics 2026-04-16 Leroy Cronin , Sara I. Walker

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

Recently, Batusov and Soutchanski proposed a notion of actual achievement cause in the situation calculus, amongst others, they can determine the cause of quantified effects in a given action history. While intuitively appealing, this…

Artificial Intelligence · Computer Science 2026-05-13 Daxin Liu , Vaishak Belle

Actual causation is concerned with the question "what caused what?" Consider a transition between two states within a system of interacting elements, such as an artificial neural network, or a biological brain circuit. Which combination of…

Artificial Intelligence · Computer Science 2019-01-11 Larissa Albantakis , William Marshall , Erik Hoel , Giulio Tononi

This is an examination of some methods that learn causations in event sequences. A causation is defined as a conjunction of one or more cause events occurring in an arbitrary order, with possible intervening non-causal events, that lead to…

Machine Learning · Computer Science 2024-12-16 Thomas E. Portegys
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