An argumentation-based framework for deliberation in multi-agent systems

  • Authors:
  • Santi Ontañón;Enric Plaza

  • Affiliations:
  • Cognitive Computing Lab, Georgia Institute of Technology, Atlanta, GA;Artificial Intelligence Research Institute, Spanish Council for Scientific Research, Bellaterra, Catalonia, Spain

  • Venue:
  • ArgMAS'07 Proceedings of the 4th international conference on Argumentation in multi-agent systems
  • Year:
  • 2007

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Abstract

This paper focuses of the group judgments obtained from a committee of agents that use deliberation. The deliberative process is realized by an argumentation framework called AMAL. The AMAL framework is completely based on learning from examples: the argument preference relation, the argument generation policy, and the counterargument generation policy are case-based techniques. For join deliberation, learning agents share their experience by forming a committee to decide upon some joint decision. We experimentally show that the deliberation in committees of agents improves the accuracy of group judgments. We also show that a voting scheme based on assessing the confidence of arguments improves the accuracy of group judgments than majority voting.