Abstract
Multiagent settings are usually characterized by numerous goals, diverse opinions and conflicts of interest. In order to reach understanding and achieve cooperation, agents need a means of expressing their individual arguments which may contain explanations, justifications or any other kind of information. Furthermore, existing information may usually be incomplete, inconsistent and expressed in qualitative terms. In this paper, we present an argumentation-based framework that supports defeasible and qualitative reasoning in such environments. An interval-based qualitative value logic is applied, together with an inference mechanism in order to refine agents' knowledge, check consistency and, eventually, conclude the issue. The model is currently under development in Java, the aim being to deploy it on the World Wide Web.
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Karacapilidis, N.I., Papadias, D., Gordon, T.F. (1996). An argumentation based framework for defeasible and qualitative reasoning. In: Borges, D.L., Kaestner, C.A.A. (eds) Advances in Artificial Intelligence. SBIA 1996. Lecture Notes in Computer Science, vol 1159. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61859-7_1
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DOI: https://doi.org/10.1007/3-540-61859-7_1
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