Review:

  • Authors:
  • Stella Heras;Vicente Botti;Vicente Julián

  • Affiliations:
  • Information systems and computing department, universidad politécnica de valencia, camino de vera s/n, 46022 valencia, spain;Information systems and computing department, universidad politécnica de valencia, camino de vera s/n, 46022 valencia, spain;Information systems and computing department, universidad politécnica de valencia, camino de vera s/n, 46022 valencia, spain

  • Venue:
  • The Knowledge Engineering Review
  • Year:
  • 2009

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Abstract

Nowadays, Multi-Agent Systems (MAS) are broadening their applications to open environments, where heterogeneous agents could enter into the system, form agents’ organizations and interact. The high dynamism of open MAS gives rise to potential conflicts between agents and thus, to a need for a mechanism to reach agreements. Argumentation is a natural way of harmonizing conflicts of opinion that has been applied to many disciplines, such as Case-Based Reasoning (CBR) and MAS. Some approaches that apply CBR to manage argumentation in MAS have been proposed in the literature. These improve agents’ argumentation skills by allowing them to reason and learn from experiences. In this paper, we have reviewed these approaches and identified the current contributions of the CBR methodology in this area. As a result of this work, we have proposed several open issues that must be taken into consideration to develop a CBR framework that provides the agents of an open MAS with arguing and learning capabilities.