By P.E. Dunne and T.J.M. Bench-Capon, Editors
Argumentation has developed from its unique learn basically through philosophers to emerge within the final ten years as a huge sub-discipline of synthetic Intelligence. one of the major contributions as a result of this were techniques to modeling and research of defeasible reasoning, formal bases for negotiation and discussion methods in multiagent platforms, and using argumentation conception in AI purposes whose nature isn't really top defined via conventional logics, e.g. criminal reasoning, overview of conflicting ideals, and so on. the method of studying and exploiting classical remedies of Argumentation thought in potent computational phrases has resulted in a wealthy interchange of principles between researchers from disciplines equivalent to Philosophy, Linguistics, AI and Economics. whereas paintings over fresh years has performed a lot to consolidate various contributions to the sector, many new issues were pointed out and shape the root of present study. The papers during this quantity, awarded as a part of the first foreign convention on Computational version of Arguments (COMMA) in September 2006, supply a invaluable evaluation of on-going study matters and issues inside of this box.
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Extra info for Computational Models of Argument: Proceedings of COMMA 2006
Zlotkin. Rules of encounter : designing conventions for automated negotiation among computers. MIT Press, Cambridge, MA, USA, 1994. 26 D. Kalofonos et al. / Building Agents that Plan and Argue in a Social Context  N. R. Jennings, S. Parsons, P. Noriega, and C. Sierra. On argumentation-based negotiation. In Proceedings of International Workshop on Multi-Agent Systems (IWMAS’98), Boston, USA, 1998.  S. Parsons, C. Sierra, and N. R. Jennings. Agents that reason and negotiate by arguing. Journal of Logic and Computation, 8(3):261–292, June 1998.
Accordingly, it is our belief that agents engaged in reasoning should have access to a general purpose argumentation engine that can be conﬁgured to conform to one of a range of semantics. Our prototype argumentation engine has been built using tuProlog  as its foundation. tuProlog is a Java-based Prolog engine which has been designed from the ground up as a thin and light-weight engine that is easily deployable, dynamically conﬁgurable and easily integrated into Internet or agent applications .
It follows that, by constructing an arbitrary tree, all preferred extensions can be enumerated. 3. Encoding Graphs For the agents to conclude on the best compromise , a formal language for expressing graphs and properties of graphs must be deﬁned. For efﬁciency reasons we aim to make this language ﬁnite and as small as possible, while ensuring that it is still sufﬁciently powerful to describe any graph and its membership status in . First, we introduce a small language for encoding graphs: Deﬁnition 1 (Simple Graph Language).