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Related papers: Defaults and Normality in Causal Structures

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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

Understanding the root cause of a defect is critical to isolating and repairing buggy behavior. We present Causal Testing, a new method of root-cause analysis that relies on the theory of counterfactual causality to identify a set of…

Software Engineering · Computer Science 2020-02-20 Brittany Johnson , Yuriy Brun , Alexandra Meliou

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

Structural causal models are the basic modelling unit in Pearl's causal theory; in principle they allow us to solve counterfactuals, which are at the top rung of the ladder of causation. But they often contain latent variables that limit…

Artificial Intelligence · Computer Science 2021-11-23 Marco Zaffalon , Alessandro Antonucci , Rafael Cabañas

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

In recent years the search for a proper formal definition of actual causation -- i.e., the relation of cause-effect as it is instantiated in specific observations, rather than general causal relations -- has taken on impressive proportions.…

Artificial Intelligence · Computer Science 2015-03-04 Sander Beckers , 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

The design of scientific experiments deserves its own variation of formal verification to catch cases where scientists made important mistakes, such as forgetting to take confounding variables into account. One of the most fundamental…

Programming Languages · Computer Science 2026-04-27 Anna Zhang , Qinglan Luo , London Bielicke , Eunice Jun , Adam Chlipala

Causation has been the issue of philosophic debate since Hippocrates. Recent work defines actual causation in terms of Pearl/Halpern's causality framework, formalizing necessary causes (IJCAI'15). This has inspired causality notions in the…

Artificial Intelligence · Computer Science 2017-10-26 Robert Künnemann

Interpretability research on large language models (LLMs) has yielded important insights into model behaviour, yet recurring pitfalls persist: findings that do not generalise, and causal interpretations that outrun the evidence. Our…

Machine Learning · Computer Science 2026-03-20 Shruti Joshi , Aaron Mueller , David Klindt , Wieland Brendel , Patrik Reizinger , Dhanya Sridhar

We study the complexity of satisfiability problems in probabilistic and causal reasoning. Given random variables $X_1, X_2,\ldots$ over finite domains, the basic terms are probabilities of propositional formulas over atomic events $X_i =…

Computational Complexity · Computer Science 2025-04-29 Markus Bläser , Julian Dörfler , Maciej Liśkiewicz , Benito van der Zander

To appear in Theory and Practice of Logic Programming (TPLP). In this paper we propose an extension of logic programming (LP) where each default literal derived from the well-founded model is associated to a justification represented as an…

Logic in Computer Science · Computer Science 2016-05-11 Pedro Cabalar , Jorge Fandinno

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

This paper presents a simple generalization of causal consistency suited to any object defined by a sequential specification. As causality is captured by a partial order on the set of operations issued by the processes on shared objects…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-02-05 Achour Mostéfaoui , Matthieu Perrin , Michel Raynal

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

I generalize acyclic deterministic structural causal models to the nondeterministic case and argue that this offers an improved semantics for counterfactuals. The standard, deterministic, semantics developed by Halpern (and based on the…

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

The classical causal relations between a set of variables, some observed and some latent, can induce both equality constraints (typically conditional independences) as well as inequality constraints (Instrumental and Bell inequalities being…

Quantum Physics · Physics 2024-04-11 Shashaank Khanna , Marina Maciel Ansanelli , Matthew F. Pusey , Elie Wolfe

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

Contextuality was originally defined only for consistently connected systems of random variables (those without disturbance/signaling). Contextuality-by-Default theory (CbD) offers an extension of the notion of contextuality to…

Quantum Physics · Physics 2023-04-12 Ehtibar Dzhafarov , Janne V. Kujala

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