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

Authors:
Santiago Ontaòón;Enric Plaza
Affiliations:
Artificial Intelligence Research Institute IIIA-CSIC, Campus UAB, 08193 Bellaterra, Catalonia, Spain. E-mail: {santi,enric}@iiia.csic.es;Artificial Intelligence Research Institute IIIA-CSIC, Campus UAB, 08193 Bellaterra, Catalonia, Spain. E-mail: {santi,enric}@iiia.csic.es
Venue:
Multiagent and Grid Systems
Year:
2011

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Abstract

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 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.