- -

Robustness, stability, recoverability, and reliability in constraint satisfaction problems

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Robustness, stability, recoverability, and reliability in constraint satisfaction problems

Mostrar el registro sencillo del ítem

Ficheros en el ítem

dc.contributor.author Barber Sanchís, Federico es_ES
dc.contributor.author Salido Gregorio, Miguel Angel es_ES
dc.date.accessioned 2016-07-28T10:25:19Z
dc.date.available 2016-07-28T10:25:19Z
dc.date.issued 2015-09
dc.identifier.issn 0219-1377
dc.identifier.uri http://hdl.handle.net/10251/68385
dc.description The final publication is available at Springer via http://dx.doi.org/10.1007/s10115-014-0778-3 es_ES
dc.description.abstract Many real-world problems in Artificial Intelligence (AI) as well as in other areas of computer science and engineering can be efficiently modeled and solved using constraint programming techniques. In many real-world scenarios the problem is partially known, imprecise and dynamic such that some effects of actions are undesired and/or several un-foreseen incidences or changes can occur. Whereas expressivity, efficiency and optimality have been the typical goals in the area, there are several issues regarding robustness that have a clear relevance in dynamic Constraint Satisfaction Problems (CSP). However, there is still no clear and common definition of robustness-related concepts in CSPs. In this paper, we propose two clearly differentiated definitions for robustness and stability in CSP solutions. We also introduce the concepts of recoverability and reliability, which arise in temporal CSPs. All these definitions are based on related well-known concepts, which are addressed in engineering and other related areas. es_ES
dc.description.sponsorship This work has been partially supported by the research project TIN2013-46511-C2-1 (MINECO, Spain). We would also thank the reviewers for their efforts and helpful comments. en_EN
dc.language Inglés es_ES
dc.publisher Springer es_ES
dc.relation.ispartof Knowledge and Information Systems es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Constraint satisfaction problems es_ES
dc.subject Robustness es_ES
dc.subject Stability es_ES
dc.subject Dynamic CSPs es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title Robustness, stability, recoverability, and reliability in constraint satisfaction problems es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s10115-014-0778-3
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//TIN2013-46511-C2-1-P/ES/TECNICAS INTELIGENTES PARA LA OBTENCION DE SOLUCIONES ROBUSTAS Y EFICIENTES ENERGETICAMENTE EN SCHEDULING: APLICACION AL TRANSPORTE::UPV/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escola Tècnica Superior d'Enginyeria Informàtica es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Técnica Superior de Ingeniería del Diseño - Escola Tècnica Superior d'Enginyeria del Disseny es_ES
dc.description.bibliographicCitation Barber Sanchís, F.; Salido Gregorio, MA. (2015). Robustness, stability, recoverability, and reliability in constraint satisfaction problems. Knowledge and Information Systems. 44(3):719-734. https://doi.org/10.1007/s10115-014-0778-3 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://link.springer.com/article/10.1007/s10115-014-0778-3 es_ES
dc.description.upvformatpinicio 719 es_ES
dc.description.upvformatpfin 734 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 44 es_ES
dc.description.issue 3 es_ES
dc.relation.senia 269360 es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES
dc.description.references Abril M, Barber F, Ingolotti L, Salido MA, Tormos P, Lova A (2008) An assessment of railway capacity. Transp Res Part E 44(5):774–806 es_ES
dc.description.references Barber F (2000) Reasoning on intervals and point-based disjunctive metric constraints in temporal contexts. J Artif Intell Res 12:35–86 es_ES
dc.description.references Bartak R, Salido MA (2011) Constraint satisfaction for planning and scheduling problems. Constraints 16(3):223–227 es_ES
dc.description.references Bertsimas D, Sim M (2004) The price of robustness. Oper Res 52(1):35–53 es_ES
dc.description.references Climent L, Wallace R, Salido M, Barber F (2013) Modeling robustness in CSPS as weighted CSPS. In: Integration of AI and OR techniques in constraint programming for combinatorial optimization problems CPAIOR 2013, pp 44–60 es_ES
dc.description.references Climent L, Wallace R, Salido M, Barber F (2014) Robustness and stability in constraint programming under dynamism and uncertainty. J Artif Intell Res 49(1):49–78 es_ES
dc.description.references Dechter R (1991) Temporal constraint network. Artif Intell 49:61–295 es_ES
dc.description.references Hazewinkel M (2002) Encyclopaedia of mathematics. Springer, New York es_ES
dc.description.references Hebrard E (2007) Robust solutions for constraint satisfaction and optimisation under uncertainty. PhD thesis, University of New South Wales es_ES
dc.description.references Hebrard E, Hnich B, Walsh T (2004) Super solutions in constraint programming. In: Integration of AI and OR techniques in constraint programming for combinatorial optimization problems (CPAIOR-04), pp 157–172 es_ES
dc.description.references Jen E (2003) Stable or robust? What’s the difference? Complexity 8(3):12–18 es_ES
dc.description.references Kitano H (2007) Towards a theory of biological robustness. Mol Syst Biol 3(137) es_ES
dc.description.references Liebchen C, Lbbecke M, Mhring R, Stiller S (2009) The concept of recoverable robustness, linear programming recovery, and railway applications. In: LNCS, vol 5868 es_ES
dc.description.references Papapetrou P, Kollios G, Sclaroff S, Gunopulos D (2009) Mining frequent arrangements of temporal intervals. Knowl Inf Syst 21:133–171 es_ES
dc.description.references Rizk A, Batt G, Fages F, Solima S (2009) A general computational method for robustness analysis with applications to synthetic gene networks. Bioinformatics 25(12):168–179 es_ES
dc.description.references Rossi F, van Beek P, Walsh T (2006) Handbook of constraint programming. Elsevier, New York es_ES
dc.description.references Roy B (2010) Robustness in operational research and decision aiding: a multi-faceted issue. Eur J Oper Res 200:629–638 es_ES
dc.description.references Szathmary E (2006) A robust approach. Nature 439:19–20 es_ES
dc.description.references Verfaillie G, Schiex T (1994) Solution reuse in dynamic constraint satisfaction problems. In: Proceedings of the 12th national conference on artificial intelligence (AAAI-94), pp 307–312 es_ES
dc.description.references Wallace R, Grimes D, Freuder E (2009) Solving dynamic constraint satisfaction problems by identifying stable features. In: Proceedings of international joint conferences on artificial intelligence (IJCAI-09), pp 621–627 es_ES
dc.description.references Wang D, Tse Q, Zhou Y (2011) A decentralized search engine for dynamic web communities. Knowl Inf Syst 26(1):105–125 es_ES
dc.description.references Wiggins S (1990) Introduction to applied nonlinear dynamical systems and chaos. Springer, New York es_ES
dc.description.references Zhou Y, Croft W (2008) Measuring ranked list robustness for query performance prediction. Knowl Inf Syst 16:155–171 es_ES


Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem