Physical Sciences › Computer Science › Artificial Intelligence
Logic, Reasoning, and Knowledge
169 artículos indexados
Los trabajos reunidos bajo este tema exploran cómo los sistemas de inteligencia artificial pueden manipular reglas, razonamientos y conocimientos de manera formal. Abordan cuestiones como la validación de restricciones lógicas (OWL, SHACL), la transformación de consultas (Horn-ALCHI, GQL) o la gestión de información incompleta o contradictoria, apoyándose en marcos teóricos como la prueba automática, las ontologías o las distribuciones probabilísticas. El desafío consiste en estructurar razonamientos robustos, ya sea en abducción, diagnóstico o preservación de propiedades lógicas durante transformaciones, al tiempo que se integran nociones como la incertidumbre o las elecciones metafísicas subyacentes a los modelos.
Este asunto y su jerarquía proceden de la clasificación OpenAlex, el catálogo abierto de la investigación científica mundial.
Volumen mensual - últimos 12 meses
Países de los laboratorios
- Estados Unidos28 % · 24 artículos
- Alemania16 % · 14 artículos
- China9,4 % · 8 artículos
- Reino Unido7,1 % · 6 artículos
- Italia7,1 % · 6 artículos
- España5,9 % · 5 artículos
- Austria5,9 % · 5 artículos
- Sudáfrica3,5 % · 3 artículos
Sobre 85 artículos de este tema con al menos un laboratorio localizado. 34 países representados.
Se trata del país del laboratorio, nunca de la nacionalidad de las personas. Un artículo firmado desde varios países cuenta para cada uno de ellos, por lo que las partes suman más del 100 %. La cobertura es parcial y el vacío no es aleatorio: un investigador cuya institución se desconoce suele publicar poco, lo que sobrerrepresenta a los laboratorios consolidados.
Últimos artículos
- What Was Said, Not What Was 'Thought': Type-6 Logic for CoT Verification
Adrian de Wynter · 1 de octubre de 2026
We introduce Type-6 logic, a variant of dynamic epistemic logic augmented with two operators (uncertainty and recurrence), designed to model the inferential dynamics of contemporary large language model (LLM) chain-of-thought (CoT) reasoning. Type-6 accounts for common LLM reasoning pathologies such…
- Abductive World Modeling via Causal Representation Learning
Ziqi Liu, Songhan Yang, Linfan Zhou, Jiatong Liu, Lijun Peng, Long Wan, Yinqi Bai · 30 de septiembre de 2026
The central challenge of world modeling is to learn representations that capture how the world evolves. However, existing world models predominantly represent future states without explicitly capturing the latent causes underlying their evolution, limiting their ability to reason about why and how t…
- Proofs Without Nominals: G\"odel's Ontological Argument, its Shallow Embedding, and the Open Questions of the Monatshefte Notes
Christoph Benzm\"uller · 30 de septiembre de 2026
The shallow embedding of higher-order modal logic in classical higher-order logic, used in Benzm\"uller and Scott's Notes on G\"odel's and Scott's variants of the ontological argument (2025), reaches beyond the modal object language of the arguments: its property quantifiers range over terms that ma…
- Decidable Reasoning About Time in Finite-Domain Situation Calculus Theories
Till Hofmann, Stefan Schupp, Gerhard Lakemeyer · 23 de septiembre de 2026
Representing time is crucial for cyber-physical systems and has been studied extensively in the situation calculus. The most commonly used approach represents time by adding a real-valued function $\mathit{time}(a)$ that attaches a time point to each action and consequently to each situation. We sho…
- Stable Marriage Problems with Ties and Incomplete Preferences: An Empirical Comparison of ASP, SAT, ILP, CP, and Local Search Methods
Selin Eyupoglu, Muge Fidan, Yavuz Gulesen, Ilayda Begum Izci, Berkan Teber, Baturay Yilmaz, Ahmet Alkan, Esra Erdem · 23 de septiembre de 2026
We study a variation of the Stable Marriage problem, where every man and every woman express their preferences as preference lists which may be incomplete and contain ties. This problem is called the Stable Marriage problem with Ties and Incomplete preferences (SMTI). We consider three optimization …
- PAA: The Probabilistic Allen Algebra: A Generative and Complete Probabilistic Extension of Allen's Interval Relations
Julian Eggert (Honda Research Institute Europe, Offenbach, Germany) · 18 de septiembre de 2026
Allen's interval algebra is a qualitative calculus for temporal relations, but its thirteen base relations are crisp predicates over exact interval boundaries. This is inadequate for temporal information from language, perception, databases, or uncertain histories, where times, durations, and bounda…
- Semantic Knowledge Technologies: what the Semantic Web lost sight of, and what it never had
Achille Zappa · 15 de septiembre de 2026
The Semantic Web set out to give information a machine-interpretable form so that software could integrate and reason over it. Its standards became scientific knowledge infrastructure, but the machine competence it promised did not follow, and the systems now answering questions over scientific know…
- The Semantic Elevation Operator and the Closure of the Undecidable Class under Preservation
Jose Pascual Gumbau Mezquita · 11 de septiembre de 2026
The undecidability of a program's static semantic properties is governed by Rice's theorem. Self-modifying systems, however, require analysing not whether a property holds now, but whether it is preserved when the system rewrites itself. We formalise this transition through a semantic elevation oper…
- Monadic Second-Order Logic in HOL: Deep and Shallow with Automated Faithfulness (Extended Preprint)
Christoph Benzmueller, Daniel Kirchner · 9 de septiembre de 2026
In Isabelle/HOL, we apply the deep-and-shallow embedding methodology of our prior work to monadic second-order logic (MSO). Three embeddings are developed side by side: a deep embedding (an inductive datatype with an explicit satisfaction relation); a maximal-shallow embedding that translates the co…
- Three Types of Negation of Triple and its Elements and an Extension of Triple
Zhenghua Pan · 9 de septiembre de 2026
In various data models, the classical triple is a typical semantic data model. However, due to the design of the triple as a simple structure for representing positive assertions, it cannot sufficiently express different forms of negation present in the triple and its elements. This paper conceptual…
- Modus Tollens and Counterfactuals and Counterfactual Reasoning Based on Three Types of Negation
Zhenghua Pan · 9 de septiembre de 2026
Modus Tollens (MT) is a classical logical inference rule, while counterfactuals are hypothetical statements that are contrary to facts, and counterfactual reasoning is a process of reasoning based on counterfactuals. Negation is an indispensable core concept in them. In this paper, based on the logi…
- Relative Prime Factorization and Finite-State Presentations under Fixed Finite-Monoid Observation
Takayuki Kuriyama · 4 de septiembre de 2026
Let $L\subseteq\Sigma^*$ and fix a morphism $h:\Sigma^*\to M$ into a finite monoid. We study exact factorization and canonical presentation in the relative syntactic congruence $\theta_{L,h}:=\equiv_L\cap\ker h$. We separate unique factorization from finite direct presentation. An exhaustively com…
- Causal-Counterfactual RAG: The Integration of Causal-Counterfactual Reasoning into RAG
Harshad Khadilkar, Abhay Gupta · 4 de septiembre de 2026
Large language models (LLMs) have transformed natural language processing (NLP), enabling diverse applications by integrating large-scale pre-trained knowledge. However, their static knowledge limits dynamic reasoning over external information, especially in knowledge-intensive domains. Retrieval-Au…
- Evidential-Based Higher-Order Set Argumentation Framework
Shuai Tang · 31 de agosto de 2026
Evidential argumentation extends Dung's abstract argumentation by requiring arguments and interactions to be backed by chains of evidence rooted in prima-facie elements. However, existing formalisms lack a unified treatment of evidential support, higher-order relations (attacks and supports targetin…
- Context Localization for Generalized Level-Based Evaluation in Knowledge-Based Systems
Ondrej Hutn\'{i}k, Nat\'{a}lia Pu\v{s}k\'{a}rov\'{a} · 31 de agosto de 2026
We study context localization for generalized level-based evaluation in knowledge-based systems. The framework models situations where a structured nonnegative score, defined on facts, rules, cases, criteria or evidence units, is evaluated through conditional aggregation tests on admissible knowledg…
- Compositional Generalization via Structural Identification in a Category-Theoretic Framework
Akihiro Maeda, Thomas Seiller, Yohei Oseki · 28 de agosto de 2026
Compositional generalization is usually evaluated through model accuracy. We instead ask which structural or lexical identifications make held-out COGS examples admissible from the structures observed in training. Sentences are represented as functors from syntactic addresses to lexical tokens, and …
- The Imperfective Paradox Is Not Necessarily in Large Language Models: A Benchmark Failure Before a Model Failure
Kaiqiao Han, Yizhou Sun · 27 de agosto de 2026
The imperfective paradox provides a useful test of compositional semantic analysis. Recent work constructs an NLI benchmark and reports that models frequently infer completed telic events from progressive descriptions, attributing this behavior to a Teleological Bias. It further argues that promptin…
- A Mathematical Theory of Interpretation: Rational Entropy, Spectral Readout, and Confusability as a Resource
Blake Reynolds · 26 de agosto de 2026
This article presents the abridged core of \emph{A Mathematical Theory of Interpretation} (MTI), which treats interpretation as observer-relative spectral measurement under an access structure. MTI makes interpretation a method-design problem: access, query, utility, and medium determine what an obs…
- Distinguishing Revision and Delayed Elaboration in Incremental Narrative Interpretation
Yi-Chun Chen · 25 de agosto de 2026
Both human and AI systems that process narrative or long-form content operate incrementally: input is received over time, and internal representations must be updated accordingly. Incremental interpretation, therefore, depends not only on what is represented but also on how the representational stat…
- Identifying Implicit Premises for Logical Reconstruction of Argument Graphs
Xuyao Feng, Anthony Hunter · 20 de agosto de 2026
The logical reconstruction of argument graphs from natural language text is challenging because of the prevalence of enthymemes (i.e., arguments with implicit premises). There are natural language processing methods for identifying enthymemes in text, and there are symbolic methods based on abductio…
- Formal Verification of Romanov's Triplet Logic: A Verified Filter for Sliding-window 3-CNF with Application to Structured Formulas
Dmitry V. Alexandrov · 20 de agosto de 2026
We present the first mechanised formalisation of Romanov's Triplet Logic (TLS) in the Rocq proof assistant. TLS is a triplet-based combinatorial framework for reasoning about compatible paths through layered triplet structures, called Compact Triplets Structures (CTS), and their intersection via Rom…
- Syntactic Simplification of OWL Class Expressions
Alkid Baci, N'Dah Jean Kouagou, Caglar Demir, Axel-Cyrille Ngonga Ngomo · 20 de agosto de 2026
Class expression learning often produces complex OWL class expressions that are difficult to interpret and reason over. However, by following theoretically grounded simplification principles, this complexity can be reduced. In this paper, we propose Class Expression Simplifier (CES), a novel algorit…
- Pairwise Logical Selection of Enthymeme Completions under Semantic-Link Uncertainty
Xuyao Feng, Antonis Bikakis · 20 de agosto de 2026
Arguments often omit premises or claims, forming enthymemes. We study pairwise logical selection between two candidates for the omitted component. Existing natural language methods can identify or generate candidates but often do not expose how the selected candidate completes the inference, while l…
- Preference Reasoning under Indeterminacy in Large Language Models
Hadi Hosseini, Samarth Khanna, Xiyuan Wang · 20 de agosto de 2026
As large language models evolve into decision-making agents, the ability to reason over preferences becomes fundamental to alignment, coordination, and collective intelligence. Yet, unlike standard benchmarks, real-world preference reasoning is inherently indeterminate: information may be incomplete…
- RDFdL: Integrating RDF with Differential Dynamic Logic
Yuyang Li, Lukas Kubelka, Julia Butte, Tobias K\"afer · 20 de agosto de 2026
Knowledge graphs modeled in RDF are powerful for describing static knowledge, but they cannot capture or reason about the dynamic behavior of physical systems, e.g., systems described by differential equations, which is a critical gap for AI-driven cyber-physical systems. To solve this, we propose R…
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