Using Argument Features to Improve the Argumentation Process

MAXIMILIANO BUDAN; GERARDO I. SIMARI; GUILLERMO R. SIMARI

Potsdam

Conferencia; International Conference on Computational Models of Argument; 2016

University of Potsdam

Argumentation has become an important topic in artificial intelligence; the basic idea is to identify arguments in favor and against a statement, select theacceptable ones, and determine whether the original statement can be accepted ornot ? argumentation theory thus provides reasoning mechanisms able to handle contradictory and incomplete information related to specific issues. However, the arguments involved in an argumentative discussion may have different relevance degrees; for this reason, argumentation frameworks need to represent the qualities that describe the soundness of an argument in order to refine the acceptability process performed over the argumentation model. In this work we present an abstract argumentation framework to model two independent kinds of interaction ? support and conflict ? between arguments and to represent distinctive information associated with the arguments, thus expanding the representation capability of the arguments involved. This enables (i) a deeper, more detailed analysis of the relations between the arguments, (ii) an optimization of the generated argumentation model by means of an inspection of the influence of the arguments involved, and (iii) an enhancement of the semantics through the availability of more information about argument acceptability.