|Título||Learning, Information Exchange, and Joint-Deliberation through Argumentation in Multi-agent Systems|
|Publication Type||Book Chapter|
|Year of Publication||2008|
|Authors||Ontañón S, Plaza E|
|Editor||Meersman R, Tari Z, Herrero P|
|Book Title||On the Move to Meaningful Internet Systems: OTM 2008. OTM 2008 Confederated International Conferences, CoopIS, DOA, GADA, IS, and ODBASE 2008|
Case-Based Reasoning (CBR) can give agents the capability of learning from their own experience and solve new problems, however, in a multi-agent system, the ability of agents to collaborate is also crucial. In this paper we present an argumentation framework (AMAL) designed to provide learning agents with collaborative problem solving (joint deliberation) and information sharing capabilities (learning from communication). We will introduce the idea of CBR multi-agent systems ( systems), outline our argumentation framework and provide several examples of new tasks that agents in a system can undertake thanks to the argumentation processes.
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