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Título

An argumentation framework for learning, information exchange, and joint-deliberation in multi-agent systems

AutorOntañon, Santiago; Plaza, Enric
Palabras claveArgumentation framework
Multi-agent systems
Fecha de publicación2011
EditorIOS Press
CitaciónMultiagent and Grid Systems 7: 95- 108 (2011)
ResumenCase-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 (MAC systems), outline our argumentation framework and provide several examples of new tasks that agents in a MAC system can undertake thanks to the argumentation processes. © 2011 - IOS Press and the authors. All rights reserved.
URIhttp://hdl.handle.net/10261/138178
DOI10.3233/MGS-2011-0169
Identificadoresdoi: 10.3233/MGS-2011-0169
issn: 1574-1702
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