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In this work, we argue that ignorance can be inherently understood as a hyperintensional notion. When faced with two logically or necessarily equivalent propositions, an agent may be ignorant of one while not of the other. To capture…

Logic · Mathematics 2026-03-11 Ekaterina Kubyshkina , Mattia Petrolo

Classical logics of knowledge and belief are usually interpreted on Kripke models, for which a mathematically well-developed model theory is available. However, such models are inadequate to capture dynamic phenomena. Therefore, epistemic…

Logic in Computer Science · Computer Science 2015-03-13 Lorenz Demey

Levesque introduced a notion of ``only knowing'', with the goal of capturing certain types of nonmonotonic reasoning. Levesque's logic dealt with only the case of a single agent. Recently, both Halpern and Lakemeyer independently attempted…

Artificial Intelligence · Computer Science 2007-05-23 Joseph Y. Halpern , Gerhard Lakemeyer

As deep neural models in NLP become more complex, and as a consequence opaque, the necessity to interpret them becomes greater. A burgeoning interest has emerged in rationalizing explanations to provide short and coherent justifications for…

Computation and Language · Computer Science 2024-05-21 Neema Kotonya , Francesca Toni

Dung's abstract argumentation theory is a widely used formalism to model conflicting information and to draw conclusions in such situations. Hereby, the knowledge is represented by so-called argumentation frameworks (AFs) and the reasoning…

Artificial Intelligence · Computer Science 2016-04-01 Ringo Baumann , Thomas Linsbichler , Stefan Woltran

The foundations of formal models for epistemic and doxastic logics often rely on certain logical aspects of modal logics such as S4 and S4.2 and their semantics; however, the corresponding mathematical results are often stated in papers or…

Logic in Computer Science · Computer Science 2024-04-24 Laura P. Gamboa Guzman , Kristin Y. Rozier

An answer set is a plain set of literals which has no further structure that would explain why certain literals are part of it and why others are not. We show how argumentation theory can help to explain why a literal is or is not contained…

Artificial Intelligence · Computer Science 2020-02-19 Claudia Schulz , Francesca Toni

This paper offers an approach to extensible knowledge representation and reasoning for a family of formalisms known as Description Logics. The approach is based on the notion of adding new concept constructors, and includes a heuristic…

Artificial Intelligence · Computer Science 2011-05-30 A. Borgida

Inthispaperwedescribeaconcept-wisemulti-preferencesemantics for description logic which has its root in the preferential approach for modeling defeasible reasoning in knowledge representation. We argue that this proposal, beside satisfying…

Artificial Intelligence · Computer Science 2020-09-03 Laura Giordano , Valentina Gliozzi , Daniele Theseider Dupré

In the present paper, the existence and multiplicity problems of extensions are addressed. The focus is on extension of the stable type. The main result of the paper is an elegant characterization of the existence and multiplicity of…

Artificial Intelligence · Computer Science 2007-05-23 Bart Verheij

Legal judgment prediction (LJP) has become increasingly important in the legal field. In this paper, we identify that existing large language models (LLMs) have significant problems of insufficient reasoning due to a lack of legal…

Artificial Intelligence · Computer Science 2025-08-25 Xinyu Yang , Chenlong Deng , Zhicheng Dou

Common sense suggests that when individuals explain why they believe something, we can arrive at more accurate conclusions than when they simply state what they believe. Yet, there is no known mechanism that provides incentives to elicit…

Computer Science and Game Theory · Computer Science 2025-02-20 Siddarth Srinivasan , Ezra Karger , Michiel Bakker , Yiling Chen

Causality is an important concept both for proving impossibility results and for synthesizing efficient protocols in distributed computing. For asynchronous agents communicating over unreliable channels, causality is well studied and…

Multiagent Systems · Computer Science 2019-07-23 Roman Kuznets , Laurent Prosperi , Ulrich Schmid , Krisztina Fruzsa

Proof-theoretic semantics, and base-extension semantics in particular, can be seen as a logical realization of inferentialism, in which the meaning of expressions is understood through their use. We present a base-extension semantics for…

Logic · Mathematics 2025-08-01 Timo Eckhardt , David J. Pym

Humans are black boxes -- we cannot observe their neural processes, yet society functions by evaluating verifiable arguments. AI explainability should follow this principle: stakeholders need verifiable reasoning chains, not mechanistic…

Machine Learning · Computer Science 2025-10-07 Ege Cakar , Per Ola Kristensson

Justification theory is an abstract unifying formalism that captures semantics of various non-monotonic logics. One intriguing problem that has received significant attention is the consistency problem: under which conditions are…

Artificial Intelligence · Computer Science 2022-08-08 Simon Marynissen , Bart Bogaerts

The paper investigates an evidence-based semantics for epistemic logics. It is shown that the properties of knowledge obtained from a potentially infinite body of evidence are described by modal logic S5. At the same time, the properties of…

Logic in Computer Science · Computer Science 2021-06-23 Pavel Naumov , Jia Tao

There has been an increasing interest in topological semantics for epistemic logic, which has been shown to be useful for, e.g., modelling evidence, degrees of belief, and self-reference. We introduce a polytopological PDL capable of…

Logic in Computer Science · Computer Science 2026-02-17 Martín Diéguez , David Fernández-Duque

We consider dynamic versions of epistemic logic as formulated in Baltag and Moss "Logics for epistemic programs" (2004). That paper proposed a logical language (actually families of languages parameterized by action signatures) for dynamic…

Logic in Computer Science · Computer Science 2022-03-15 Alexandru Baltag , Lawrence S. Moss , Slawomir Solecki

This study investigates an explainable reasoning method for financial decision-making based on knowledge-enhanced large language model agents. To address the limitations of traditional financial decision methods that rely on parameterized…

Computation and Language · Computer Science 2025-12-11 Qingyuan Zhang , Yuxi Wang , Cancan Hua , Yulin Huang , Ning Lyu