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We study situations where a group of voters need to take a collective decision over a number of public issues, with the goal of getting a result that reflects the voters' opinions in a proportional manner. Our focus is on interconnected…

Computer Science and Game Theory · Computer Science 2025-09-25 Julian Chingoma , Umberto Grandi , Arianna Novaro

Inference is the process of using facts we know to learn about facts we do not know. A theory of inference gives assumptions necessary to get from the former to the latter, along with a definition for and summary of the resulting…

Machine Learning · Statistics 2021-09-27 Beau Coker , Cynthia Rudin , Gary King

This paper studies axioms for nonmonotonic consequences from a semantics-based point of view, focusing on a class of mathematical structures for reasoning about partial information without a predefined syntax/logic. This structure is called…

Logic in Computer Science · Computer Science 2007-05-23 Guo-Qiang Zhang

Axiomatization has been widely used for testing logical implications. This paper suggests a non-axiomatic method, the chase, to test if a new dependency follows from a given set of probabilistic dependencies. Although the chase computation…

Artificial Intelligence · Computer Science 2013-02-18 Michael S. K. M. Wong

Probabilities of causation provide explanatory information on the observed occurrence (causal necessity) and non-occurrence (causal sufficiency) of events. Here, we adapt these probabilities (probability of necessity, probability of…

Quantitative Methods · Quantitative Biology 2025-04-28 Bronner P. Gonçalves

The ability to accurately interpret implied meanings plays a crucial role in human communication and language use, and language models are also expected to possess this capability. This study demonstrates that providing language models with…

Computation and Language · Computer Science 2025-11-20 Takuma Sato , Seiya Kawano , Koichiro Yoshino

After surveying classical results, we introduce a generalized notion of inference system to support structural recursion on non-well-founded data types. Besides axioms and inference rules with the usual meaning, a generalized inference…

Logic in Computer Science · Computer Science 2018-04-23 Francesco Dagnino

It is claimed that a variety of facts concerning ellipsis, event reference, and interclausal coherence can be explained by two features of the linguistic form in question: (1) whether the form leaves behind an empty constituent in the…

cmp-lg · Computer Science 2008-02-03 Andrew Kehler

As complex machine learning models continue to find applications in high-stakes decision-making scenarios, it is crucial that we can explain and understand their predictions. Post-hoc explanation methods provide useful insights by…

Machine Learning · Statistics 2024-10-16 Beepul Bharti , Paul Yi , Jeremias Sulam

A fundamental question asked in modal logic is whether a given theory is consistent. But consistent with what? A typical way to address this question identifies a choice of background knowledge axioms (say, S4, D, etc.) and then shows the…

Logic · Mathematics 2023-07-12 Samuel Allen Alexander , Arthur Paul Pedersen

Case-based reasoning is known to play an important role in several legal settings. In this paper we focus on a recent approach to case-based reasoning, supported by an instantiation of abstract argumentation whereby arguments represent…

Artificial Intelligence · Computer Science 2023-10-31 Guilherme Paulino-Passos , Francesca Toni

Exposure mappings facilitate investigations of complex causal effects when units interact in experiments. Current methods require experimenters to use the same exposure mappings both to define the effect of interest and to impose…

Statistics Theory · Mathematics 2023-03-14 Fredrik Sävje

We introduce an axiomatic approach to entropies and relative entropies that relies only on minimal information-theoretic axioms, namely monotonicity under mixing and data-processing as well as additivity for product distributions. We find…

Information Theory · Computer Science 2021-09-22 Gilad Gour , Marco Tomamichel

Accurately predicting the relevance of items to users is crucial to the success of many social platforms. Conventional approaches train models on logged historical data; but recommendation systems, media services, and online marketplaces…

Machine Learning · Computer Science 2022-10-11 Amir Feder , Guy Horowitz , Yoav Wald , Roi Reichart , Nir Rosenfeld

The features of a logically sound approach to a theory of statistical reasoning are discussed. A particular approach that satisfies these criteria is reviewed. This is seen to involve selection of a model, model checking, elicitation of a…

Statistics Theory · Mathematics 2018-05-09 Luai Al-Labadi , Zeynep Baskurt , Michael Evans

Logical relations (LR) have been around for many years, and today they are used in many formal results. However, it can be difficult to LR beginners to find a good place to start to learn. Papers often use highly specialized LRs that use…

Programming Languages · Computer Science 2019-07-26 Lau Skorstengaard

In this paper, we provide more evidence for the contention that logical consequence should be understood in normative terms. Hartry Field and John MacFarlane covered the classical case. We extend their work, examining what it means for an…

Logic in Computer Science · Computer Science 2014-02-20 Julio Lemos

This paper discusses system consequence, a central idea in the project to lift the theory of information flow to the abstract level of universal logic and the theory of institutions. The theory of information flow is a theory of distributed…

Logic in Computer Science · Computer Science 2018-10-09 Robert E. Kent

Complex reasoning problems are most clearly and easily specified using logical rules, but require recursive rules with aggregation such as count and sum for practical applications. Unfortunately, the meaning of such rules has been a…

Databases · Computer Science 2023-08-29 Yanhong A. Liu , Scott D. Stoller

Definitions and notations with historical references are given for some numerical coefficients commonly used to quantify relations among collections of objects for the purpose of expressing approximate knowledge and probabilistic reasoning.

Artificial Intelligence · Computer Science 2013-04-11 Silvio Ursic