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Related papers: (De-)Composing Causality in Labeled Transition Sys…

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We introduce an approach to counterfactual inference based on merging information from multiple datasets. We consider a causal reformulation of the statistical marginal problem: given a collection of marginal structural causal models (SCMs)…

Artificial Intelligence · Computer Science 2022-07-18 Luigi Gresele , Julius von Kügelgen , Jonas M. Kübler , Elke Kirschbaum , Bernhard Schölkopf , Dominik Janzing

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

Rewriting logic is naturally concurrent: several subterms of the state term can be rewritten simultaneously. But state terms are global, which makes compositionality difficult to achieve. Compositionality here means being able to decompose…

Logic in Computer Science · Computer Science 2020-01-31 Óscar Martín , Alberto Verdejo , Narciso Martí-Oliet

One of the basic sanity properties of a behavioural semantics is that it constitutes a congruence with respect to standard process operators. This issue has been traditionally addressed by the development of rule formats for transition…

Logic in Computer Science · Computer Science 2010-08-13 Maciej Gazda , Wan Fokkink

We explore "omitted label contexts," in which training data is limited to a subset of the possible labels. This setting is standard among specialized human experts or specific, focused studies. By studying Simpson's paradox, we observe that…

Machine Learning · Computer Science 2025-05-02 Bijan Mazaheri , Siddharth Jain , Matthew Cook , Jehoshua Bruck

In general relativity, `causal structure' refers to the partial order on space-time points (or regions) that encodes time-like relationships. Recently, quantum information and quantum foundations saw the emergence of a `causality…

Quantum Physics · Physics 2017-08-16 Aleks Kissinger , Matty Hoban , Bob Coecke

Within the decoherence theory we investigate the physical background of the condition of the separability (diagonalizability in noncorrelated basis) of the interaction Hamiltonian of the composite system, "system plus environment". It…

Quantum Physics · Physics 2007-05-23 M. Dugic

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

Counterfactual reasoning, a cornerstone of human cognition and decision-making, is often seen as the 'holy grail' of causal learning, with applications ranging from interpreting machine learning models to promoting algorithmic fairness.…

Machine Learning · Computer Science 2025-04-11 Yahya Aalaila , Gerrit Großmann , Sumantrak Mukherjee , Jonas Wahl , Sebastian Vollmer

Principle of information causality, proposed as a generalization of no signaling principle, has efficiently been applied to outcast beyond quantum correlations as unphysical. In this letter we show that this principle when utilized properly…

Complex information-processing systems, for example quantum circuits, cryptographic protocols, or multi-player games, are naturally described as networks composed of more basic information-processing systems. A modular analysis of such…

Quantum Physics · Physics 2017-04-27 Christopher Portmann , Christian Matt , Ueli Maurer , Renato Renner , Björn Tackmann

In this paper, we continue our research on the algorithmic aspects of Halpern and Pearl's causes and explanations in the structural-model approach. To this end, we present new characterizations of weak causes for certain classes of causal…

Artificial Intelligence · Computer Science 2013-01-07 Thomas Eiter , Thomas Lukasiewicz

Causality is vital for understanding true cause-and-effect relationships between variables within predictive models, rather than relying on mere correlations, making it highly relevant in the field of Explainable AI. In an automated…

Machine Learning · Computer Science 2024-08-28 Arturo Fredes , Jordi Vitria

Interventional causal models describe several joint distributions over some variables used to describe a system, one for each intervention setting. They provide a formal recipe for how to move between the different joint distributions and…

Machine Learning · Statistics 2021-08-06 Eigil F. Rischel , Sebastian Weichwald

MITL is a temporal logic that facilitates the verification of real-time systems by expressing the critical timing constraints placed on these systems. MITL specifications can be checked against system models expressed as networks of timed…

Logic in Computer Science · Computer Science 2025-05-12 Bernd Finkbeiner , Felix Jahn , Julian Siber

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

Hypersafety properties of arity $n$ are program properties that relate $n$ traces of a program (or, more generally, traces of $n$ programs). Classic examples include determinism, idempotence, and associativity. A number of relational…

Programming Languages · Computer Science 2022-10-31 Emanuele D'Osualdo , Azadeh Farzan , Derek Dreyer

We discuss quantum non-locality and contextuality using the notion of transition sets. This approach provides a way to obtain a direct logical contradiction with locality/non-contextuality in the EPRB gedanken experiment as well as a clear…

Quantum Physics · Physics 2007-11-19 Hans Westman

The intrinsic multivaluedness of interaction process, revealed in Part I of this series of papers, is interpreted as the origin of the true dynamical (in particular, quantum) chaos. The latter is causally deduced as unceasing series of…

Quantum Physics · Physics 2008-02-03 Andrei P. Kirilyuk

In the context of abstract argumentation, we present the benefits of considering temporality, i.e. the order in which arguments are enunciated, as well as causality. We propose a formal method to rewrite the concepts of acyclic abstract…

Artificial Intelligence · Computer Science 2024-02-07 Y. Munro , C. Sarmiento , I. Bloch , G. Bourgne , M. -J. Lesot