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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

The concept of causal nonseparability has been recently introduced, in opposition to that of causal separability, to qualify physical processes that locally abide by the laws of quantum theory, but cannot be embedded in a well-defined…

Quantum Physics · Physics 2019-02-04 Julian Wechs , Alastair A. Abbott , Cyril Branciard

We describe the interface between measure theoretic probability and causal inference by constructing causal models on probability spaces within the potential outcomes framework. We find that measure theory provides a precise and instructive…

Statistics Theory · Mathematics 2019-07-04 Irineo Cabreros , John D. Storey

Possibility theory offers a framework where both Lehmann's "preferential inference" and the more productive (but less cautious) "rational closure inference" can be represented. However, there are situations where the second inference does…

Artificial Intelligence · Computer Science 2013-02-18 Salem Benferhat , Didier Dubois , Henri Prade

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

A causal set is a partially ordered set on a countably infinite ground-set such that each element is above finitely many others. A natural extension of a causal set is an enumeration of its elements which respects the order. We bring…

Probability · Mathematics 2011-09-22 Graham Brightwell , Malwina Luczak

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

Predicting the future is an important component of decision making. In most situations, however, there is not enough information to make accurate predictions. In this paper, we develop a theory of causal reasoning for predictive inference…

Artificial Intelligence · Computer Science 2013-04-10 Thomas L. Dean , Keiji Kanazawa

Understanding and quantifying causal relationships between variables is essential for reasoning about the physical world. In this work, we develop a resource-theoretic framework to do so. Here, we focus on the simplest nontrivial setting --…

Over the past two decades, considerable strides have been made in advancing neuroscientific techniques, yet challenges remain in attributing causality to observed associations. This review addresses a fundamental issue in observational…

Other Quantitative Biology · Quantitative Biology 2025-11-04 Eric W. Bridgeford , Brian S. Caffo , Maya B. Mathur , Russell A. Poldrack

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

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

As autonomous systems rapidly become ubiquitous, there is a growing need for a legal and regulatory framework to address when and how such a system harms someone. There have been several attempts within the philosophy literature to define…

Artificial Intelligence · Computer Science 2023-01-20 Sander Beckers , Hana Chockler , 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

The concept of causality has a controversial history. The question of whether it is possible to represent and address causal problems with probability theory, or if fundamentally new mathematics such as the do-calculus is required has been…

Machine Learning · Statistics 2019-10-22 Finnian Lattimore , David Rohde

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

We investigate the generalization of causal models to the case of indeterministic causal laws that was suggested in Halpern (2000). We give an overview of what differences in modeling are enforced by this more general perspective, and…

Logic in Computer Science · Computer Science 2024-04-16 Fausto Barbero

Our article described an experiment that adjudicates between different causal accounts of Bell inequality violations by a comparison of their predictive power, finding that certain types of models that are structurally radical but…

Quantum Physics · Physics 2024-12-05 Patrick Daley , Kevin J. Resch , Robert W. Spekkens

It is often argued that bottom-up causation under a physicalist, reductionist worldview precludes free will in the libertarian sense. On the one hand, the paradigm of classical mechanics makes determinism inescapable, while on the other,…

Neurons and Cognition · Quantitative Biology 2016-10-11 Salvador Malo

We introduce a formalism for the evaluation of counterfactual queries in the framework of quantum causal models, generalising Pearl's semantics for counterfactuals in classical causal models, thus completing the last rung in the quantum…

Quantum Physics · Physics 2024-09-18 Ardra Kooderi Suresh , Markus Frembs , Eric G. Cavalcanti