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.
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Ontañón, S., Plaza, E. (2008). An Argumentation-Based Framework for Deliberation in Multi-agent Systems. In: Rahwan, I., Parsons, S., Reed, C. (eds) Argumentation in Multi-Agent Systems. ArgMAS 2007. Lecture Notes in Computer Science(), vol 4946. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78915-4_12
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DOI: https://doi.org/10.1007/978-3-540-78915-4_12
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