Abstract
The paper introduces an argumentation semantics that can deal with several challenges that arise when using abstract argumentation within multi-agent systems. The extensions are computed with respect to initial constraints that specify the desired justification state of some arguments. The constraints can come from the agent’s goals, its confidence in information from other agents or they may describe a decision context, where the agent must choose between several alternatives. The core idea behind the approach is the fact that, in order to find an extension that satisfies the constraints, an agent needs to find a suitable set of arguments to defeat.
We provide a full scenario where an auction for two items is modeled as a game where the participating agents take turns at updating an argumentation framework describing the possible states of the environment as well as the agents’ intentions. The agents’ goals and the consistency of the environment’s state are described with constraints. Our argumentation semantics is shown to provide a very natural strategy for the agents playing this game. It can also be used at the end of the game for deciding its outcome, namely the final state of the environment and the actions of the agents.
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References
Baroni, P., Giacomin, M.: Resolution-based argumentation semantics. In: Proceedings of the 2nd Conference on Computational Models of Argument (COMMA 2008), Tolouse, France, pp. 25–36 (2008)
Baroni, P., Giacomin, M., Guida, G.: SCC-recursiveness: a general schema for argumentation semantics. Artificial Intelligence 168(1-2), 162–210 (2005)
Caminada, M.: Semi-stable semantics. In: Dunne, P.E., Bench-Capon, T.J.M. (eds.) Computational Models of Argument: Proceedings of COMMA 2006, September 11-12. Frontiers in Artificial Intelligence and Applications, vol. 144, pp. 121–130. IOS Press (2006)
Caminada, M.: Comparing two unique extension semantics for formal argumentation: Ideal and eager. In: Proceedings of the 19th Benelux Conference on Artificial Intelligence (BNAIC 2007), pp. 81–87 (2007)
Caminada, M., Gabbay, D.: A logical account of formal argumentation. Studia Logica 93(2), 109–145 (2009)
Coste-Marquis, S., Devred, C., Marquis, P.: Prudent semantics for argumentation frameworks. In: Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2005), Hong-Kong, China, pp. 568–572 (2005)
Coste-Marquis, S., Devred, C., Marquis, P.: Constrained argumentation frameworks. In: Proceedings of the 10th International Conference on Practices in Knowledge Representation and Reasoning, pp. 112–122 (2006)
Dung, P.M.: On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games. Artificial Intelligence 77(2), 321–357 (1995)
Dung, P.M., Mancarella, P., Toni, F.: Computing ideal sceptical argumentation. Artificial Intelligence 171(10-15), 642–674 (2007)
Modgil, S.: Hierarchical Argumentation. In: Fisher, M., van der Hoek, W., Konev, B., Lisitsa, A. (eds.) JELIA 2006. LNCS (LNAI), vol. 4160, pp. 319–332. Springer, Heidelberg (2006)
Zhang, Z., Lin, Z.: Enhancing Dung’s Preferred Semantics. In: Link, S., Prade, H. (eds.) FoIKS 2010. LNCS, vol. 5956, pp. 58–75. Springer, Heidelberg (2010)
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Gratie, C., Florea, A.M. (2012). Argumentation Semantics for Agents. In: Cossentino, M., Kaisers, M., Tuyls, K., Weiss, G. (eds) Multi-Agent Systems. EUMAS 2011. Lecture Notes in Computer Science(), vol 7541. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34799-3_9
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DOI: https://doi.org/10.1007/978-3-642-34799-3_9
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