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dc.contributor.author	Barber Sanchís, Federico
dc.contributor.author	Salido Gregorio, Miguel Angel
dc.date.accessioned	2011-04-11T11:32:20Z
dc.date.available	2011-04-11T11:32:20Z
dc.date.issued	2011-04-11
dc.identifier.uri	http://hdl.handle.net/10251/10705
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, so 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, several is-sues regarding robustness appear with a clear relevance in dynamic constraint satisfaction problems (DCSPs). However, there is still no a 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 DCSPs. All these definitions are based on related well-known concepts addressed in engineering and other related areas.	es_ES
dc.language	Inglés	es_ES
dc.publisher	Universitat Politècnica de València	es_ES
dc.relation.ispartofseries	Informes técnicos de investigación DSIC-IA-PS;1
dc.rights	Reserva de todos los derechos	es_ES
dc.subject	Constraint satisfaction	es_ES
dc.subject	Robustness
dc.subject	Dynamic constraint satisfaction problems
dc.title	Robustness, Stability, Recoverability and Reliability in Dynamic Constraint Satisfaction Problems	es_ES
dc.type	Informe	es_ES
dc.rights.accessRights	Abierto	es_ES
dc.contributor.affiliation	Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
dc.description.bibliographicCitation	Barber Sanchís, F.; Salido Gregorio, MA. (2011). Robustness, Stability, Recoverability and Reliability in Dynamic Constraint Satisfaction Problems. http://hdl.handle.net/10251/10705	es_ES

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  IA-PS: Inteligencia Artificial, Planificacion y Scheduling

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