Abstract argumentation systems
Artificial Intelligence
On the evaluation of argumentation formalisms
Artificial Intelligence
Measures for persuasion dialogs: A preliminary investigation
Proceedings of the 2008 conference on Computational Models of Argument: Proceedings of COMMA 2008
Heuristics in Argumentation: A Game-Theoretical Investigation
Proceedings of the 2008 conference on Computational Models of Argument: Proceedings of COMMA 2008
Towards higher impact argumentation
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
On the meta-logic of arguments
ArgMAS'05 Proceedings of the Second international conference on Argumentation in Multi-Agent Systems
Journal of Logic and Computation
A Relevance-theoretic Framework for Constructing and Deconstructing Enthymemes
Journal of Logic and Computation
Arguing about preferences and decisions
ArgMAS'10 Proceedings of the 7th international conference on Argumentation in Multi-Agent Systems
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The main goal of a persuasion dialogue is to persuade, but agents may have a number of additional goals concerning the dialogue duration, how much and what information is shared or how aggressive the agent is. Several criteria have been proposed in the literature covering different aspects of what may matter to an agent, but it is not clear how to combine these criteria that are often incommensurable and partial. This paper is inspired by multi-attribute decision theory and considers argument selection as decision-making where multiple criteria matter. A meta-level argumentation system is proposed to argue about what argument an agent should select in a given persuasion dialogue. The criteria and sub-criteria that matter to an agent are structured hierarchically into a value tree and meta-level argument schemes are formalized that use a value tree to justify what argument the agent should select. In this way, incommensurable and partial criteria can be combined.