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We show that it is possible to understand and identify a decision maker's subjective causal judgements by observing her preferences over interventions. Following Pearl [2000], we represent causality using causal models (also called…

Theoretical Economics · Economics 2024-01-23 Joseph Y. Halpern , Evan Piermont

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

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

In distributed systems where strong consistency is costly when not impossible, causal consistency provides a valuable abstraction to represent program executions as partial orders. In addition to the sequential program order of each…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-03-15 Matthieu Perrin , Achour Mostefaoui , Claude Jard

As society transitions towards an AI-based decision-making infrastructure, an ever-increasing number of decisions once under control of humans are now delegated to automated systems. Even though such developments make various parts of…

Artificial Intelligence · Computer Science 2023-06-09 Drago Plecko , Elias Bareinboim

We look more carefully at the modeling of causality using structural equations. It is clear that the structural equations can have a major impact on the conclusions we draw about causality. In particular, the choice of variables and their…

Artificial Intelligence · Computer Science 2011-06-15 Joseph Y. Halpern , Christopher Hitchcock

This paper introduces a collection of four data sets, similar to Anscombe's Quartet, that aim to highlight the challenges involved when estimating causal effects. Each of the four data sets is generated based on a distinct causal mechanism:…

Methodology · Statistics 2023-07-20 Lucy D'Agostino McGowan , Travis Gerke , Malcolm Barrett

This work outlines the novel application of the empirical analysis of causation, presented by Kutach, to the study of information theory and its role in physics. The central thesis of this paper is that causation and information are…

History and Philosophy of Physics · Physics 2018-12-04 Geoff Beck

Our evolution as a species made a huge step forward when we understood the relationships between causes and effects. These associations may be trivial for some events, but they are not in complex scenarios. To rigorously prove that some…

Mathematical Software · Computer Science 2021-07-13 Martí Pedemonte , Jordi Vitrià , Álvaro Parafita

We introduce the idea of an understanding with respect to a set of clauses as a satisfying truth assignment explained by the contexts of the literals in the clauses. Following this idea, we present a mechanical process that obtains, if it…

Computational Complexity · Computer Science 2016-09-19 Alejandro Sanchez Guinea

We formulate the Hauptvermutung of Causal Set Theory in two mathematically well-defined but different ways one of which turns out to be wrong and the other one turns out to be true. A further result is that the Hauptvermutung is true if we…

Differential Geometry · Mathematics 2025-12-30 Olaf Müller

We introduce a novel framework for decomposing interventional causal effects into synergistic, redundant, and unique components, building on the intuition of Partial Information Decomposition (PID) and the principle of M\"obius inversion.…

Artificial Intelligence · Computer Science 2025-09-22 Abel Jansma

Physics is a field of science that has traditionally used the scientific method to answer questions about why natural phenomena occur and to make testable models that explain the phenomena. Discovering equations, laws and principles that…

Justification theory is a unifying semantic framework. While it has its roots in non-monotonic logics, it can be applied to various areas in computer science, especially in explainable reasoning; its most central concept is a justification:…

Artificial Intelligence · Computer Science 2020-09-23 Simon Marynissen , Bart Bogaerts , Marc Denecker

We study the problem of enumerating answers of Conjunctive Queries ranked according to a given ranking function. Our main contribution is a novel algorithm with small preprocessing time, logarithmic delay, and non-trivial space usage during…

Databases · Computer Science 2025-05-21 Shaleen Deep , Paraschos Koutris

Causal learning has garnered significant attention in recent years because it reveals the essential relationships that underpin phenomena and delineates the mechanisms by which the world evolves. Nevertheless, traditional causal learning…

Machine Learning · Computer Science 2024-07-31 Zizhen Deng , Xiaolong Zheng , Hu Tian , Daniel Dajun Zeng

Detecting commonsense causal relations (causation) between events has long been an essential yet challenging task. Given that events are complicated, an event may have different causes under various contexts. Thus, exploiting context plays…

Computation and Language · Computer Science 2023-05-10 Zhaowei Wang , Quyet V. Do , Hongming Zhang , Jiayao Zhang , Weiqi Wang , Tianqing Fang , Yangqiu Song , Ginny Y. Wong , Simon See

The paper proposes a fresh look at the concept of goal and advances that motivational attitudes like desire, goal and intention are just facets of the broader notion of (acceptable) outcome. We propose to encode the preferences of an agent…

Logic in Computer Science · Computer Science 2022-09-13 Guido Governatori , Francesco Olivieri , Simone Scannapieco , Antonino Rotolo , Matteo Cristani

The results presented in this paper are refinements of some results presented in a previous paper. Three such refined results are presented. The first one relaxes one of the basic hypotheses assumed in the previous paper, and thus extends…

Complex Variables · Mathematics 2015-05-06 Jorge L. deLyra

Expanding upon recent work, a new class of $A$-functions is introduced that can be viewed as an appropriate generalization of the class of regular $A$-functions, the class of structured $A$-functions, and the class of perfect $A$-functions.…

Number Theory · Mathematics 2022-03-01 Joseph Burnett , Alex Taylor