Abstract
This paper deals with an approach to opponent-modelling in argumentation-based persuasion dialogues. It assumes that dialogue participants (agents) have models of their opponents’ knowledge, which can be augmented based on previous dialogues. Specifically, previous dialogues indicate relationships of support, which refer both to arguments as abstract entities and to their logical constituents. The augmentation of an opponent model relies on these relationships. An argument external to an opponent model can augment that model with its logical constituents, if that argument shares support relationships with other arguments that can be constructed from that model. The likelihood that the constituents of supporting arguments will in fact be known to an opponent, varies according to support types. We therefore provide corresponding quantifications for each support type.
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Notes
- 1.
Note that if agents play logically perfectly they can be shown to win iff the argument they move is justified under the grounded respectively preferred semantics in the framework constructed during the dialogue [9].
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Hadjinikolis, C., Modgil, S., Black, E. (2015). Building Support-Based Opponent Models in Persuasion Dialogues. In: Black, E., Modgil, S., Oren, N. (eds) Theory and Applications of Formal Argumentation. TAFA 2015. Lecture Notes in Computer Science(), vol 9524. Springer, Cham. https://doi.org/10.1007/978-3-319-28460-6_8
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