An Argumentation-Based Framework for Deliberation in Multi-agent Systems

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.