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Related papers: Applying Constraint Handling Rules to HPSG

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In this paper we continue the work on our extension of Answer Set Programming by non-Herbrand functions and add to the language support for arithmetic expressions and various inequality relations over non-Herbrand functions, as well as…

Artificial Intelligence · Computer Science 2013-01-09 Marcello Balduccini , Michael Gelfond

While pre-trained language models (PLMs) are the go-to solution to tackle many natural language processing problems, they are still very limited in their ability to capture and to use common-sense knowledge. In fact, even if information is…

Artificial Intelligence · Computer Science 2021-09-28 Mohammed Saeed , Naser Ahmadi , Preslav Nakov , Paolo Papotti

This paper presents a verification framework based on a new class of predicate Constraint Satisfaction Problems called pCSP where constraints are represented as clauses modulo first-order theories over function variables and predicate…

Programming Languages · Computer Science 2020-07-08 Hiroshi Unno , Yuki Satake , Tachio Terauchi , Eric Koskinen

Probabilistic Hoare logic (PHL) is an extension of Hoare logic and is specifically useful in verifying randomized programs. It allows researchers to formally reason about the behavior of programs with stochastic elements, ensuring the…

Logic in Computer Science · Computer Science 2024-06-25 Xin Sun , Xingchi Su , Xiaoning Bian , Anran Cui

One recurring problem in program development is that of understanding how to re-use code developed by a third party. In the context of (constraint) logic programming, part of this problem reduces to figuring out how to query a program. If…

Programming Languages · Computer Science 2007-05-23 Andy King , Lunjin Lu

Probabilistic behavior is omnipresent in computer controlled systems, in particular, so-called safety-critical hybrid systems, because of various reasons, like uncertain environments, or fundamental properties of nature. In this paper, we…

Formal Languages and Automata Theory · Computer Science 2021-01-04 Fujun Wang , Zining Cao , Lixing Tan , Zhen Li

Conventional representation learning methods learn a universal representation that primarily captures dominant semantics, which may not always align with customized downstream tasks. For instance, in animal habitat analysis, researchers…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Honglin Liu , Chao Sun , Peng Hu , Yunfan Li , Xi Peng

The controller state and reference governor (CSRG) is an add-on scheme for nominal closed-loop systems with dynamic controllers which supervises the controller internal state and the reference input to the closed-loop system to enforce…

Systems and Control · Electrical Eng. & Systems 2020-10-06 Nan Li , Anouck Girard , Ilya Kolmanovsky

ECLiPSe is a Prolog-based programming system, aimed at the development and deployment of constraint programming applications. It is also used for teaching most aspects of combinatorial problem solving, e.g. problem modelling, constraint…

Programming Languages · Computer Science 2010-12-21 Joachim Schimpf , Kish Shen

The Rust programming language has garnered significant interest and use as a modern, type-safe, memory-safe, and potentially formally analyzable programming language. Our interest in Rust stems from its potential as a hardware/software…

Logic in Computer Science · Computer Science 2022-05-25 David Hardin

We shift the QCSP (Quantified Constraint Satisfaction Problems) framework to the QCHR (Quantified Constraint Handling Rules) framework by enabling dynamic binder and access to user-defined constraints. QCSP offers a natural framework to…

Artificial Intelligence · Computer Science 2019-09-19 Vincent Barichard , Igor Stéphan

The Shapes Constraint Language (SHACL) has been recently introduced as a W3C recommendation to define constraints that can be validated against RDF graphs. Interactions of SHACL with other Semantic Web technologies, such as ontologies or…

Artificial Intelligence · Computer Science 2020-08-10 Paolo Pareti , George Konstantinidis , Timothy J. Norman , Murat Şensoy

Much recent research has been devoted to modeling effects within type theory. Building on this work, we observe that effectful type theories can provide a foundation on which to build semantics for more complex programming constructs and…

Programming Languages · Computer Science 2021-12-01 Nikhil Swamy , Aseem Rastogi , Aymeric Fromherz , Denis Merigoux , Danel Ahman , Guido Martínez

This paper presents the constrained Hybrid Metaheuristic (cHM) algorithm as a general framework for continuous optimisation. Unlike many existing metaheuristics that are tailored to specific function classes or problem domains, cHM is…

Neural and Evolutionary Computing · Computer Science 2026-03-20 Piotr A. Kowalski , Szymon Kucharczyk , Jacek Mańdziuk

Recent advances in reinforcement learning from human feedback (RLHF) and preference optimization have substantially improved the usability, coherence, and safety of large language models. However, recurring behaviors such as performative…

Artificial Intelligence · Computer Science 2026-05-13 William Parris

ConArg is a Constraint Programming-based tool that can be used to model and solve different problems related to Abstract Argumentation Frameworks (AFs). To implement this tool we have used JaCoP, a Java library that provides the user with a…

Artificial Intelligence · Computer Science 2013-01-17 Stefano Bistarelli , Francesco Santini

Higher-order constructs extend the expressiveness of first-order (Constraint) Logic Programming ((C)LP) both syntactically and semantically. At the same time assertions have been in use for some time in (C)LP systems helping programmers…

Programming Languages · Computer Science 2014-06-03 Nataliia Stulova , José F. Morales , Manuel V. Hermenegildo

User queries in real-world recommendation systems often combine structured constraints (e.g., category, attributes) with unstructured preferences (e.g., product descriptions or reviews). We introduce HyST (Hybrid retrieval over…

Information Retrieval · Computer Science 2025-08-26 Jiyoon Myung , Jihyeon Park , Joohyung Han

We study a hybrid conditional gradient - smoothing algorithm (HCGS) for solving composite convex optimization problems which contain several terms over a bounded set. Examples of these include regularization problems with several norms as…

Optimization and Control · Mathematics 2014-04-16 Andreas Argyriou , Marco Signoretto , Johan Suykens

Inductive reasoning is a core problem-solving capacity: humans can identify underlying principles from a few examples, which robustly generalize to novel scenarios. Recent work evaluates large language models (LLMs) on inductive reasoning…

Machine Learning · Computer Science 2024-06-03 Ruocheng Wang , Eric Zelikman , Gabriel Poesia , Yewen Pu , Nick Haber , Noah D. Goodman