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Argument-based persuasion dialogues provide an effective mechanism for agents to communicate their beliefs, and their reasons for those beliefs, in order to convince another agent of some topic argument. In such dialogues, the persuader has strategic considerations, and must decide which of its known arguments should be asserted, and the order in which they should be asserted. Recent works consider mechanisms for determining an optimal strategy for persuading the responder. However, computing such strategies is expensive, swiftly becoming impractical as the number of arguments increases. In response, we present a strategy that uses heuristic information of the domain arguments and can be computed with high numbers of arguments. Our results show that not only is the heuristic strategy fast to compute, it also performs significantly better than a random strategy.
|Title of host publication
|Computational Models of Argument
|Subtitle of host publication
|Proceedings of COMMA 2016
|411 - 418
|Frontiers in Artificial Intelligence and Applications 287
|Published - 2016
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- 1 Finished
1/05/2015 → 30/06/2016