Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Bayesian reasoning in an abductive mechanism for argument generation and analysis
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Exploratory Interaction with a Bayesian Argumentation System
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
A process model for recognizing communicative acts and modeling negotiation subdialogues
Computational Linguistics
Arguing about planning alternatives
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 3
Generating information-sharing subdialogues in expert-user consultation
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Recognizing intentions from rejoinders in a Bayesian interactive argumentation system
PRICAI'00 Proceedings of the 6th Pacific Rim international conference on Artificial intelligence
Natural Language Processing and User Modeling: Synergies and Limitations
User Modeling and User-Adapted Interaction
Exploiting Uncertainty and Incomplete Knowledge in Deceptive Argumentation
ICCS '01 Proceedings of the International Conference on Computational Sciences-Part I
An Integrated Approach for Generating Arguments and Rebuttals and Understanding Rejoinders
UM '01 Proceedings of the 8th International Conference on User Modeling 2001
A Probabilistic Approach for Argument Interpretation
User Modeling and User-Adapted Interaction
Recognizing intentions from rejoinders in a Bayesian interactive argumentation system
PRICAI'00 Proceedings of the 6th Pacific Rim international conference on Artificial intelligence
Improving the presentation of argument interpretations based on user trials
AI'04 Proceedings of the 17th Australian joint conference on Advances in Artificial Intelligence
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We describe a mechanism which generates rebuttals to a user's rejoinders in the context of arguments generated from Bayesian networks. This mechanism is implemented in an interactive argumentation system. Given an argument generated by the system and an interpretation of a user's rejoinder, the generation of the rebuttal takes into account the intended effect of the user's rejoinder, determined on a model of the user's beliefs, and its actual effect, determined on a model of the system's beliefs. We consider three main rebuttal strategies: refute the user's rejoinder, strengthen the argument goal, and dismiss the user's line of reasoning.