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Multi-adjoint logic programming is a general framework with interesting features, which involves other positive logic programming frameworks such as monotonic and residuated logic programming, generalized annotated logic programs, fuzzy…

Logic in Computer Science · Computer Science 2024-09-25 M. Eugenia Cornejo , David Lobo , Jesús Medina

A logical model of spatiotemporal structures is pictured as a succession of processes in time. One usual way to formalize time structure is to assume the global existence of time points and then collect some of them to form time intervals…

Logic · Mathematics 2009-11-13 Kenji Tokuo

We present a new approach to enhancing Answer Set Programming (ASP) with Constraint Processing techniques which allows for solving interesting Constraint Satisfaction Problems in ASP. We show how constraints on finite domains can be…

Logic in Computer Science · Computer Science 2010-07-26 Christian Drescher , Toby Walsh

Timed automata (TA) is used for modeling systems with timing aspects. A TA extends a finite automaton with a set of real valued variables called clocks, that measure the time and constraints over the clocks guard the transitions. A…

Formal Languages and Automata Theory · Computer Science 2021-04-20 Ebru Aydin Gol

We continue the investigation of parameterized extensions of Linear Temporal Logic (LTL) that retain the attractive algorithmic properties of LTL: a polynomial space model checking algorithm and a doubly-exponential time algorithm for…

Logic in Computer Science · Computer Science 2015-09-25 Martin Zimmermann

The use of spatio-temporal logics in control is motivated by the need to impose complex spatial and temporal behavior on dynamical systems, and to control these systems accordingly. Synthesizing correct-by-design control laws is a…

Formal Languages and Automata Theory · Computer Science 2020-03-26 Lars Lindemann , Dimos V. Dimarogonas

While many advances in time series models focus exclusively on numerical data, research on multimodal time series, particularly those involving contextual textual information, remains in its infancy. With recent progress in large language…

Machine Learning · Computer Science 2026-03-10 Zihao Li , Xiao Lin , Zhining Liu , Jiaru Zou , Ziwei Wu , Lecheng Zheng , Dongqi Fu , Yada Zhu , Hendrik Hamann , Hanghang Tong , Jingrui He

The static ``train then deploy" paradigm fundamentally limits Large Language Models (LLMs) from dynamically adapting their weights in response to continuous streams of new information inherent in real-world tasks. Test-Time Training (TTT)…

Machine Learning · Computer Science 2026-04-08 Guhao Feng , Shengjie Luo , Kai Hua , Ge Zhang , Di He , Wenhao Huang , Tianle Cai

Dynamic systems in AI are often complex and heterogeneous, so that an internal specification is not accessible and verification techniques such as model checking are not applicable. Monitoring is in such cases an attractive alternative, as…

Artificial Intelligence · Computer Science 2026-05-15 Alessandro Gianola , Marco Montali , Sarah Winkler

Mechanized verification of liveness properties for infinite programs with effects and nondeterminism is challenging. Existing temporal reasoning frameworks operate at the level of models such as traces and automata. Reasoning happens at a…

Programming Languages · Computer Science 2025-08-22 Eleftherios Ioannidis , Yannick Zakowski , Steve Zdancewic , Sebastian Angel

Frontier AI models have achieved remarkable progress, yet recent studies suggest they struggle with compositional reasoning, often performing at or below random chance on established benchmarks. We revisit this problem and show that widely…

Artificial Intelligence · Computer Science 2026-04-27 Yinglun Zhu , Jiancheng Zhang , Fuzhi Tang

Constraint answer set programming is a promising research direction that integrates answer set programming with constraint processing. It is often informally related to the field of satisfiability modulo theories. Yet, the exact formal link…

Logic in Computer Science · Computer Science 2017-02-27 Yuliya Lierler , Benjamin Susman

Temporal logics are an obvious high-level descriptive companion formalism to dynamical systems which model behavior as deterministic evolution of state over time. A wide variety of distinct temporal logics applicable to dynamical systems…

Logic in Computer Science · Computer Science 2012-12-11 Baltasar Trancón y Widemann

The paper presents probabilistic extensions of interval temporal logic (ITL) and duration calculus (DC) with infinite intervals and complete Hilbert-style proof systems for them. The completeness results are a strong completeness theorem…

Logic in Computer Science · Computer Science 2019-03-14 Dimitar P. Guelev

Justification logics are modal-like logics with the additional capability of recording the reason, or justification, for modalities in syntactic structures, called justification terms. Justification logics can be seen as explicit…

Logic in Computer Science · Computer Science 2017-03-08 Samuel Bucheli , Meghdad Ghari , Thomas Studer

We propose an approach to formally specifying the behavioral properties of systems that rely on a perception model for interactions with the physical world. The key idea is to introduce embeddings -- mathematical representations of a…

Artificial Intelligence · Computer Science 2025-03-07 Parv Kapoor , Abigail Hammer , Ashish Kapoor , Karen Leung , Eunsuk Kang

Answer set programming (ASP) is an efficient problem-solving approach, which has been strongly supported both scientifically and technologically by several solvers, ongoing active research, and implementations in many different fields.…

Artificial Intelligence · Computer Science 2021-09-20 Ezgi Iraz Su

The use of non-deterministic functions is a distinctive feature of modern functional logic languages. The semantics commonly adopted is call-time choice, a notion that at the operational level is related to the sharing mechanism of lazy…

Programming Languages · Computer Science 2009-03-13 Francisco Javier Lopez-Fraguas , Juan Rodriguez-Hortala , Jaime Sanchez-Hernandez

Transferring high-level knowledge from a source task to a target task is an effective way to expedite reinforcement learning (RL). For example, propositional logic and first-order logic have been used as representations of such knowledge.…

Artificial Intelligence · Computer Science 2019-09-11 Zhe Xu , Ufuk Topcu

We consider temporal numeric planning problems $\Pi$ expressed in PDDL2.1 level 3, and show how to produce SMT formulas $(i)$ whose models correspond to valid plans of $\Pi$, and $(ii)$ that extend the recently proposed planning with…

Artificial Intelligence · Computer Science 2024-12-19 Matteo Cardellini , Enrico Giunchiglia