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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