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dc.date.accessioned 2012-10-11T12:11:10Z
dc.date.available 2012-10-11T12:11:10Z
dc.date.issued 1999
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/22256
dc.description.abstract There has been an increasing demand of a variety of logical systems, prompted by applications of logic in Al, logic prograrnming and other related areas. Labelled Deductive Systems (LDS) [Gab96] were developed as a flexible methodology to formalize such a kind of complex logical systems. In the last decade, defeasible argumentation [SL92, PV99, Ver96, BDKT97] has proven to be a confluence point for many approaches to formalizing commonsense reasoning. Different formalisms have been developed, many of them sharing cornmon fe atures. This paper outlines an argumentative LDS, in which the main issues concerning defeasible argumentation are captured within a unified logical framework. The proposed framework is defined in two stages. First, defeasible inference will be formalized by characterizing a defeasible LDS. That system wiU be then extended in order to obtain an argumentative LDS. en
dc.language en es
dc.subject defeasible argumentation en
dc.subject ARTIFICIAL INTELLIGENCE es
dc.subject labelled deductive systems en
dc.title The role of labelled deductive systems in a formal system for defeasible argumentation en
dc.type Objeto de conferencia es
sedici.creator.person Chesñevar, Carlos Iván es
sedici.creator.person Simari, Guillermo Ricardo es
sedici.description.note Eje: Aspectos teóricos de la inteligencia artificial es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Red de Universidades con Carreras en Informática (RedUNCI) es
sedici.subtype Objeto de conferencia es
sedici.rights.license Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
sedici.rights.uri http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
sedici.date.exposure 1999-05 es
sedici.relation.event I Workshop de Investigadores en Ciencias de la Computación es
sedici.description.peerReview peer-review es


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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)