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Default logic encounters some conceptual difficulties in representing common sense reasoning tasks. We argue that we should not try to formulate modular default rules that are presumed to work in all or most circumstances. We need to take…

Artificial Intelligence · Computer Science 2013-02-08 Choh Man Teng

Neural rationale models are popular for interpretable predictions of NLP tasks. In these, a selector extracts segments of the input text, called rationales, and passes these segments to a classifier for prediction. Since the rationale is…

Computation and Language · Computer Science 2022-07-26 Yiming Zheng , Serena Booth , Julie Shah , Yilun Zhou

In this article, we employ mathematical concepts as a tool to examine the phenomenon of consciousness experience and logical phenomena. Through our investigation, we aim to demonstrate that our experiences, while not confined to…

Neurons and Cognition · Quantitative Biology 2024-01-23 Kazem Haghnejad Azar

In this paper, following an elementary line of thought which somewhat differs from the usual one, we prove once more that any deterministic theory predictively equivalent to quantum mechanics unavoidably exhibits a contextual character. The…

Quantum Physics · Physics 2009-11-13 GianCarlo Ghirardi , Karl Wienand

The "mind-brain supervenience" conjecture suggests that all mental properties are derived from the physical properties of the brain. To address the question of whether the mind supervenes on the brain, we frame a supervenience hypothesis in…

Other Quantitative Biology · Quantitative Biology 2011-08-09 Joshua T. Vogelstein , R. Jacob Vogelstein , Carey E. Priebe

In this article, we review selective inference, a set of techniques for inference when the statistical question asked is a function of the data. This setting often arises in contemporary scientific workflows, where hypotheses and parameters…

Methodology · Statistics 2026-04-14 Anna Neufeld , Ronan Perry , Daniela Witten

Explanations of cognitive behavior often appeal to computations over representations. What does it take for a system to implement a given computation over suitable representational vehicles within that system? We argue that the language of…

Machine Learning · Computer Science 2025-08-18 Atticus Geiger , Jacqueline Harding , Thomas Icard

This note is concerned with a formal analysis of the problem of non-monotonic reasoning in intelligent systems, especially when the uncertainty is taken into account in a quantitative way. A firm connection between logic and probability is…

Artificial Intelligence · Computer Science 2013-04-05 Hung-Trung Nguyen

We analyze selected iterated conditionals in the framework of conditional random quantities. We point out that it is instructive to examine Lewis's triviality result, which shows the conditions a conditional must satisfy for its probability…

Probability · Mathematics 2020-03-17 Giuseppe Sanfilippo , Angelo Gilio , David Over , Niki Pfeifer

Presupposition projection in conditionals is central to theories of meaning and pragmatics, yet it remains largely unevaluated in large language models. We address this gap through a parallel behavioral study comparing human judgments and…

Computation and Language · Computer Science 2026-05-19 Tara Azin , Yongan Yu , Raj Singh , Olessia Jouravlev

Explainability is emerging as a key requirement for autonomous systems. While many works have focused on what constitutes a valid explanation, few have considered formalizing explainability as a system property. In this work, we approach…

Logic in Computer Science · Computer Science 2025-10-21 Bernd Finkbeiner , Julian Siber

Counterfactual explanations are gaining prominence within technical, legal, and business circles as a way to explain the decisions of a machine learning model. These explanations share a trait with the long-established "principal reason"…

Computers and Society · Computer Science 2019-12-12 Solon Barocas , Andrew D. Selbst , Manish Raghavan

We present a general logical framework for reasoning about agents' cognitive attitudes of both epistemic type and motivational type. We show that it allows us to express a variety of relevant concepts for qualitative decision theory…

Artificial Intelligence · Computer Science 2023-06-22 Emiliano Lorini

Human beings possess the most sophisticated computational machinery in the known universe. We can understand language of rich descriptive power, and communicate in the same environment with astonishing clarity. Two of the many contributors…

Computation and Language · Computer Science 2021-01-01 Karthikeya Ramesh Kaushik , Andrea E. Martin

We define a property of intelligent systems, which we call Reflexivity. In human beings, it is one aspect of consciousness, and an element of deliberation. We propose a conjecture, that this property is conditioned by a topological property…

Artificial Intelligence · Computer Science 2016-04-29 Pascal Faudemay

I think that the main reason why we do not understand the general principles of how knowledge works (and probably also the reason why we have not yet designed and built efficient machines capable of artificial intelligence), is not the…

Artificial Intelligence · Computer Science 2014-04-21 Devis Pantano

Linear Logic and Defeasible Logic have been adopted to formalise different features relevant to agents: consumption of resources, and reasoning with exceptions. We propose a framework to combine sub-structural features, corresponding to the…

Artificial Intelligence · Computer Science 2018-09-12 Francesco Olivieri , Guido Governatori , Matteo Cristani , Nick van Beest , Silvano Colombo-Tosatto

In this work we first illustrate the subjective theory of de Finetti. We recall the notion of coherence for both the betting scheme and the penalty criterion, by considering the unconditional and conditional cases. We show the equivalence…

Probability · Mathematics 2023-01-24 Angelo Gilio , Giuseppe Sanfilippo

Tableaux originate as a decision method for a logical language. They can also be extended to obtain a structure that spells out all the information in a set of sentences in terms of truth value assignments to atomic formulas that appear in…

cmp-lg · Computer Science 2008-02-03 Pablo Gervas

Recent work has unveiled a theory for reasoning about the decisions made by binary classifiers: a classifier describes a Boolean function, and the reasons behind an instance being classified as positive are the prime-implicants of the…

Artificial Intelligence · Computer Science 2021-05-14 Niku Gorji , Sasha Rubin