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By Leila Amgoud, Yannis Dimopoulos, Pavlos Moraitis (auth.), Iyad Rahwan, Simon Parsons, Chris Reed (eds.)

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Extra resources for Argumentation in Multi-Agent Systems: 4th International Workshop, ArgMAS 2007, Honolulu, HI, USA, May 15, 2007, Revised Selected and Invited Papers

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MIT Press, Cambridge (1996) 3. : On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games. Artificial Intelligence 77(2), 321–358 (1995) 4. : Logical systems for defeasible argumentation. , Guenther, F.

Using similarity criteria to make trade-offs in automated negotiations. Artificial Intelligence 142(2), 205–237 (2002) 5. : Agents that reason and negotiate by arguing. Journal of Logic and Computation 8(3), 261–292 (1998) 6. : Argumentation based negotiation. Knowledge Engineering Review 18(4), 343– 375 (2003) 7. : Towards interest-based negotiation. , Yokoo, M. ) Proceedings of the 2nd International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2003), pp. 773–780. ACM Press, New York (2003) Co-argumentation Artifact for Agent Societies Enrico Oliva1 , Peter McBurney2 , and Andrea Omicini1 1 Alma Mater Studiorum–Universit` a di Bologna, Cesena, Italy 2 University of Liverpool, Liverpool L69 3BX UK Abstract.

Our algorithm is based over a standard backtracking strategy. The constraint is the absence of conflicts among arguments (undercut, rebuttal). A solution is consistent if the set of arguments satisfies the constraints. In order to limit the degree of backtracking, consistency is checked before each argument is added to the solution. When the consistency check fails, the algorithm stores partial results, and starts backtracking. Then, it recursively tries to add all the remaining arguments. In order to limit the size of the search space a branching strategy is used in the phase of set instantiation.

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