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This article fits in the area of research that investigates the application of topological duality methods to problems that appear in theoretical computer science. One of the eventual goals of this approach is to derive results in…

Logic in Computer Science · Computer Science 2022-01-05 Mehdi Zaïdi

A class of interval-based temporal languages for uniformly representing and reasoning about actions and plans is presented. Actions are represented by describing what is true while the action itself is occurring, and plans are constructed…

Artificial Intelligence · Computer Science 2011-05-30 A. Artale , E. Franconi

Modal description logics feature modalities that capture dependence of knowledge on parameters such as time, place, or the information state of agents. E.g., the logic S5-ALC combines the standard description logic ALC with an S5-modality…

Logic in Computer Science · Computer Science 2017-05-24 Paul Wild , Lutz Schröder

Mathematical reasoning has long been a key benchmark for evaluating large language models. Although substantial progress has been made on math word problems, the need for reasoning over tabular data in real-world applications has been…

Artificial Intelligence · Computer Science 2026-04-20 Shi-Yu Tian , Zhi Zhou , Wei Dong , Kun-Yang Yu , Ming Yang , Zi-Jian Cheng , Lan-Zhe Guo , Yu-Feng Li

In this paper, we present an abstract framework of many-valued modal logic with the interpretation of atomic propositions and modal operators as predicate lifting over coalgebras for an endofunctor on the category of sets. It generalizes…

Logic in Computer Science · Computer Science 2022-10-25 Chun-Yu Lin , Churn-Jung Liau

This paper presents a Prolog-based reasoning module to generate counterfactual explanations given the predictions computed by a black-box classifier. The proposed symbolic reasoning module can also resolve what-if queries using the…

Machine Learning · Computer Science 2022-11-21 Gonzalo Nápoles , Fabian Hoitsma , Andreas Knoben , Agnieszka Jastrzebska , Maikel Leon Espinosa

Augmented Language Models (ALMs) blend the reasoning capabilities of Large Language Models (LLMs) with tools that allow for knowledge retrieval and action execution. Existing ALM systems trigger LLM thought processes while pulling…

Computation and Language · Computer Science 2023-05-31 Binfeng Xu , Zhiyuan Peng , Bowen Lei , Subhabrata Mukherjee , Yuchen Liu , Dongkuan Xu

We study nested conditions, a generalization of first-order logic to a categorical setting, and provide a tableau-based (semi-decision) procedure for checking (un)satisfiability and finite model generation. This generalizes earlier results…

Logic in Computer Science · Computer Science 2024-07-10 Lara Stoltenow , Barbara König , Sven Schneider , Andrea Corradini , Leen Lambers , Fernando Orejas

This paper describes an architecture for robots that combines the complementary strengths of probabilistic graphical models and declarative programming to represent and reason with logic-based and probabilistic descriptions of uncertainty…

Robotics · Computer Science 2018-09-24 Mohan Sridharan , Michael Gelfond , Shiqi Zhang , Jeremy Wyatt

We introduce proper display calculi for basic monotonic modal logic,the conditional logic CK and a number of their axiomatic extensions. These calculi are sound, complete, conservative and enjoy cut elimination and subformula property. Our…

This thesis introduces the "method of structural refinement", which serves as a means of transforming the relational semantics of a modal and/or constructive logic into an 'economical' proof system by connecting two proof-theoretic…

Logic in Computer Science · Computer Science 2021-08-02 Tim Lyon

We introduce a proper multi-type display calculus for bilattice logic (with conflation) for which we prove soundness, completeness, conservativity, standard subformula property and cut-elimination. Our proposal builds on the product…

Logic · Mathematics 2017-09-08 Giuseppe Greco , Fei Liang , Alessandra Palmigiano , Umberto Rivieccio

This paper proposes an alternative to standard first-order logic that seeks greater naturalness, generality, and semantic self-containment. The system removes the first-order restriction, avoids type hierarchies, and dispenses with external…

Logic · Mathematics 2025-08-12 Mauro Avon

The system of Type PDL ($\tau$PDL) is an extension of Propositional Dynamic Logic (PDL) and its main goal is to provide a formal basis for reasoning about types of actions (modeled by their preconditions and effects) and agent capabilities.…

Logic in Computer Science · Computer Science 2019-09-04 Agathoklis Kritsimallis , Ioannis Refanidis

This paper depicts an algorithm for solving the Decision Boolean Satisfiability Problem using the binary numerical properties of a Special Decision Satisfiability Problem, parallel execution, object oriented, and short termination. The two…

Data Structures and Algorithms · Computer Science 2018-04-17 Carlos Barrón-Romero

Table reasoning requires models to jointly perform comprehensive semantic understanding and precise numerical operations. Although recent large language model (LLM)-based methods have achieved promising results, most of them still rely on a…

Artificial Intelligence · Computer Science 2025-12-23 Chuang Jiang , Mingyue Cheng , Xiaoyu Tao , Qingyang Mao , Jie Ouyang , Qi Liu

Basic results in combinatorial mathematics provide the foundation for a theory and calculus for reasoning about sequential behavior. A key concept of the theory is a generalization of Boolean implicant which deals with statements of the…

Logic in Computer Science · Computer Science 2007-05-23 Frederick Furtek

In the article we investigate three classes of extended Boolean Connexive Logics. Two of them are extensions of Modal and non-Modal Boolean Connexive Logics with a property of closure under an arbitrary number of negations. The remaining…

Logic · Mathematics 2024-03-20 Tomasz Jarmuzek , Jacek Malinowski , Aleksander Parol , Nicolo Zamperlin

Recent advances in the integration of deep learning with automated theorem proving have centered around the representation of logical formulae as inputs to deep learning systems. In particular, there has been a growing interest in adapting…

Artificial Intelligence · Computer Science 2020-06-08 Maxwell Crouse , Ibrahim Abdelaziz , Cristina Cornelio , Veronika Thost , Lingfei Wu , Kenneth Forbus , Achille Fokoue

LLMs often underperform on complex reasoning tasks when relying on a single generation-and-selection pipeline. Inference-time ensemble methods can improve performance by sampling diverse reasoning paths or aggregating multiple candidate…

Machine Learning · Computer Science 2026-02-03 Tong Zhu , Baiting Chen , Jin Zhou , Hua Zhou , Sriram Sankararaman , Xiaowu Dai