By Nicolas Maudet, Simon D. Parsons, Iyad Rahwan
Argumentation presents instruments for designing, imposing and studying subtle varieties of interplay between rational agents. It has made a superb contribution to the perform of multiagent dialogues. software domain names comprise: criminal disputes, enterprise negotiation, exertions disputes, workforce formation, clinical inquiry, deliberative democracy, ontology reconciliation, danger research, scheduling, and logistics.
This ebook constitutes the completely refereed post-proceedings of the 3rd foreign Workshop on Argumentation in Multi-Agent structures held in Hakodate, Japan, in may perhaps 2006 as an linked occasion of AAMAS 2006, the most overseas convention on self sufficient brokers and multi-agent systems.
The quantity opens with an unique state of the art survey paper offering the present study and supplying a finished and updated evaluate of this swiftly evolving quarter. The eleven revised articles that persist with have been rigorously reviewed and chosen from the main major workshop contributions, augmented with papers from the AAMAS 2006 major convention, in addition to from ECAI 2006, the biennial eu convention on synthetic Intelligence.
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Additional info for Argumentation in Multi-Agent Systems: Third International Workshop, ArgMAS 2006, Hakodate, Japan, May 8, 2006, Revised Selected and Invited Papers
A prototype implementation of an argument-based learning system is now going on in such a way that it is incorporated into the existing automated argument system based on EALP and LMA. Finally, we just mention worthy to pursuit future research directions. Our knowledge acquisition approaches are not intended to be used in any situation. The application of each of them is related to the type of the dialogue  occurring among agents. The detailed analysis, however, will be left to the future work.
B: I have not become thin. Mr. A: Now that you haven’t, I may not become thin either. After such an argumentation, we as well as Mr. A would usually correct or change our previous belief that the soap is eﬀective, into its contrary. Like this, we may correct wrong knowledge and learn counter-arguments. Technically, the ﬁrst assertion in Mr. A’s locution is considered as having an assumption ”the soap is eﬀective to slim”. And Mr. B argues against Mr. A. It amounts to undercut in terms of LMA. 1, we formally capture this type of learning by argumentation, calling it knowledge acquisition induced by the undercut of assumptions.
We have the sound and complete dialectical proof theory for the argumentation semantics JArgs,x/y . In the learning process described in the next section, we will often take into account deliberate or thoughtful agents who put forward deliberate arguments in the dialogue. Deﬁnition 18 (Deliberate argumentation). , KBn }, and Argsi be a set of arguments under KBi . A dialogue is called a deliberate argumentation if and only if arguments put forward in each move of the dialogue belong to JArgsi ,x/y .