Quantified Constraint Handling Rules

Autor: Vincent Barichard, Igor Stéphan

Publikováno v: Electronic Proceedings in Theoretical Computer Science, Vol 306, Iss Proc. ICLP 2019, Pp 210-223 (2019)

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 express PSPAC

Externí odkaz: https://doaj.org/article/41a177a55e5145819ce88e9c394eb20e

A Semantic Characterization ASP Base Revision

Autor: Laurent Garcia, Claire Lefèvre, Odile Papini, Igor Stéphan, Eric Würbel

Publikováno v: Journal of Artificial Intelligence Research. 66:989-1029

The paper deals with base revision for Answer Set Programming (ASP). Base revision in classical logic is done by the removal of formulas. Exploiting the non-monotonicity of ASP allows one to propose other revision strategies, namely addition strategy

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::4d0dc01cd1e600bf0b6f9042452f2f0d
https://doi.org/10.1613/jair.1.11451

First-order ASP programs as CHR programs

Autor: Igor Stéphan

Publikováno v: SAC

We present in this paper a way to use the paradigm of Answer Set Programming (ASP) into the Constraint Handling Rules (CHR) paradigm. We present a translation of the ASP language to the Constraint Handling Rules language. The committed-choice princip

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::940519e0b6749c9d0ffa466f3b17a521
https://doi.org/10.1145/3412841.3441963

A Semantic Characterization for ASP Base Revision

Autor: Odile Papini, Claire Lefèvre, Eric Würbel, Laurent Garcia, Igor Stéphan

Publikováno v: Journal of Artificial Intelligence Research
Journal of Artificial Intelligence Research, Association for the Advancement of Artificial Intelligence, 2019, 66, pp.989-1029
Journal of Artificial Intelligence Research, 2019, 66, pp.989-1029
Scalable Uncertainty Management
Scalable Uncertainty Management, Oct 2017, Granada, Spain. pp.334--347
Lecture Notes in Computer Science ISBN: 9783319675817
SUM
Scalable Uncertainty Management 2017
Scalable Uncertainty Management 2017, pp.334-347, 2017, ⟨10.1007/978-3-319-67582-4_24⟩

International audience; The paper deals with base revision for Answer Set Programming (ASP). Base revision in classical logic is done by the removal of formulas. Exploiting the non-monotonicity of ASP allows one to propose other revision strategies,

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b1a6d4d082f4bdeb5e0c5e4996f62364
https://hal-amu.archives-ouvertes.fr/hal-02392942

Computing Query Answering With Non-Monotonic Rules: A Case Study of Archaeology Qualitative Spatial Reasoning

Autor: Eric Würbel, Mohamed Ellefi, Pierre Drap, Laurent Garcia, Fabien Garreau, Claire Lefèvre, Odile Papini, Igor Stéphan

Publikováno v: 5th Global Conference on Artificial Intelligence
5th Global Conference on Artificial Intelligence, Sep 2019, Bolzano, Italy. pp.1-14
HAL

International audience; This paper deals with querying ontology-based knowledge bases equipped with non-monotonic rules through a case study within the framework of Cultural Heritage. It focuses on 3D underwater surveys on the Xlendi wreck which is r

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::5915d6725359290b79c4ea67a358606e
https://hal-amu.archives-ouvertes.fr/hal-02332016/document