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2006•Unpublished venueRequires access

Inferring acceptable arguments with Answer Set Programming

María Rosa Zapatero Osorio, Claudia Zepeda, Juan Carlos Nieves, Ulises Cortés

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Abstract

Following the argumentation framework and semantics proposed by Dung, we are interested in the problem of deciding which set of acceptable arguments support the decision making in an agent-based platform called CARREL. It is an agent-agency which mediates organ transplants. We present two possible ways to infer the stable and preferred extensions of an argumentation framework, one in a declarative way using answer set programming (ASP) and the other one in a procedure way.

About this research paper

What this paper is about

Following the argumentation framework and semantics proposed by Dung, we are interested in the problem of deciding which set of acceptable arguments support the decision making in an agent-based platform called CARREL. It is an agent-agency which mediates organ transplants. We present two possible ways to infer the stable and preferred extensions of an argumentation framework, one in a declarative way using answer set programming (ASP) and the other one in a procedure way.

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OpenAlex reports 24 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Following the argumentation framework and semantics proposed by Dung, we are interested in the problem of deciding which set of acceptable arguments support the decision making in an agent-based platform called CARREL. It is an agent-agency which mediates organ transplants. We present two possible ways to infer the stable and preferred extensions of an argumentation framework, one in a declarative way using answer set programming (ASP) and the other one in a procedure way.

Key concepts: Answer set programming, Argumentation theory, Argumentation framework, Computer science, Agency (philosophy), Semantics (computer science), Set (abstract data type), Logic programming

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