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Counterfactual reasoning aims at answering contrary-to-fact questions like ``Would have Alice recovered had she taken aspirin?'' and corresponds to the most fine-grained layer of causation. Critically, while many counterfactual statements…

Artificial Intelligence · Computer Science 2025-09-23 Lucas de Lara

I develop a novel semantics for probabilities of counterfactuals that generalizes the standard Pearlian semantics: it applies to probabilistic causal models that cannot be extended into realistic structural causal models and are therefore…

Artificial Intelligence · Computer Science 2025-12-16 Sander Beckers

The capacity to address counterfactual "what if" inquiries is crucial for understanding and making use of causal influences. Traditional counterfactual inference, under Pearls' counterfactual framework, typically depends on having access to…

Machine Learning · Computer Science 2024-02-29 Shaoan Xie , Biwei Huang , Bin Gu , Tongliang Liu , Kun Zhang

We introduce an extension of team semantics which provides a framework for the logic of manipulationist theories of causation based on structural equation models, such as Woodward's and Pearl's; our causal teams incorporate (partial or…

Logic in Computer Science · Computer Science 2019-01-04 Fausto Barbero , Gabriel Sandu

Characterising causal structure is an activity that is ubiquitous across the sciences. Causal models are representational devices that can be used as oracles for future interventions, to predict how values of some variables will change in…

Quantum Physics · Physics 2018-09-11 G. J. Milburn , Sally Shrapnel

We show that quantum oracles provide an advantage over classical oracles for answering classical counterfactual questions in causal models, or equivalently, for identifying unknown causal parameters such as distributions over functional…

Quantum Physics · Physics 2025-12-16 Ciarán M. Gilligan-Lee , Yìlè Yīng , Jonathan Richens , David Schmid

We introduce a generalization of team semantics which provides a framework for manipulationist theories of causation based on structural equation models, such as Woodward's and Pearl's; our causal teams incorporate (partial or total)…

Logic · Mathematics 2018-05-15 Fausto Barbero , Gabriel Sandu

Most of the scientific literature on causal modeling considers the structural framework of Pearl and the potential-outcome framework of Rubin to be formally equivalent, and therefore interchangeably uses do-interventions and the…

Statistics Theory · Mathematics 2024-12-17 Lucas de Lara

Bell inequalities follow from a set of seemingly natural assumptions about how to provide a causal model of a Bell experiment. In the face of their violation, two types of causal models that modify some of these assumptions have been…

Quantum Physics · Physics 2022-05-11 Patrick J. Daley , Kevin J. Resch , Robert W. Spekkens

Galles and Pearl claimed that "for recursive models, the causal model framework does not add any restrictions to counterfactuals, beyond those imposed by Lewis's [possible-worlds] framework." This claim is examined carefully, with the goal…

Artificial Intelligence · Computer Science 2013-08-20 Joseph Y. Halpern

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

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

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

Counterfactual explanations (CEs) are methods for generating an alternative scenario that produces a different desirable outcome. For example, if a student is predicted to fail a course, then counterfactual explanations can provide the…

Machine Learning · Statistics 2023-01-09 Bevan I. Smith

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 mathematically axiomatise the stochastics of counterfactuals, by introducing two related frameworks, called counterfactual probability spaces and counterfactual causal spaces, which we collectively term counterfactual spaces. They are,…

Statistics Theory · Mathematics 2026-01-05 Junhyung Park , Fanny Yang , Thomas Icard

We present a definition of cause and effect in terms of decision-theoretic primitives and thereby provide a principled foundation for causal reasoning. Our definition departs from the traditional view of causation in that causal assertions…

Artificial Intelligence · Computer Science 2014-11-17 D. Heckerman , R. Shachter

Causal Modeling Semantics (CMS, e.g., Galles and Pearl 1998; Pearl 2000; Halpern 2000) is a powerful framework for evaluating counterfactuals whose antecedent is a conjunction of atomic formulas. We extend CMS to an evaluation of the…

Logic in Computer Science · Computer Science 2023-05-01 Giuliano Rosella , Jan Sprenger

Causal reasoning is essential to science, yet quantum theory challenges it. Quantum correlations violating Bell inequalities defy satisfactory causal explanations within the framework of classical causal models. What is more, a theory…

Quantum Physics · Physics 2021-03-05 Jonathan Barrett , Robin Lorenz , Ognyan Oreshkov

We reformulate Pearl's three rules of do-calculus in the language of completely positive (CP) trace-preserving maps, thereby extending them to quantum systems with entanglement. We prove that Rule~2 fails whenever the underlying process…

Quantum Physics · Physics 2025-08-08 Jordi Vallverdu
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