Abstract
This paper describes an integrated approach for interpreting a user’s responses and generating replies in the framework of a WWW-based Bayesian argumentation system. Our system consults a user model which represents a user’s beliefs, inferences and attentional focus, as well as the system’s certainty regarding the user’s beliefs. The interpretation mechanism takes into account these factors to infer the intended effect of the user’s response on the system’s argument. The reply-generation mechanism focuses on the identification of discrepancies between the beliefs in the user model and the beliefs held by the system that are relevant to the inferred interpretation.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
J.R. Anderson. The Architecture of Cognition. Harvard University Press, Cambridge, Massachusetts, 1983.
Sandra Carberry and Lynn Lambert. A process model for recognizing communicative acts and modeling negotiation subdialogues. Computational Linguistics, 25(1):1–53, 1999.
Eugene Charniak and Robert P. Goldman. A Bayesian model of plan recognition. Artificial Intelligence, 64(1):50–56, 1993.
Abigail Gertner, Cristina Conati, and Kurt VanLehn. Procedural help in Andes: Generating hints using a Bayesian network student model. In AAAI98-Proceedings of the Fifteenth National Conference on Artificial Intelligence, pages 106–111, Madison, Wisconsin, 1998.
David Heckerman and Eric Horvitz. Inferring informational goals from free-text queries: A Bayesian approach. In Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, pages 230–237, Madison, Wisconsin, 1998.
Nathalie Jitnah, Ingrid Zukerman, Richard McConachy, and Sarah George. Towards the generation of rebuttals in a Bayesian argumentation system. In Proceedings of the First International Natural Language Generation Conference, pages 39–46, Mitzpe Ramon, Israel, 2000.
Alex Quilici. Arguing about planning alternatives. In COLING-92-Proceedings of the Fourteenth International Conference on Computational Linguistics, pages 906–910, Nantes, France, 1992.
Ingrid Zukerman, Nathalie Jitnah, Richard McConachy, and Sarah George. Recognizing intentions from rejoinders in a Bayesian interactive argumentation system. In PRICAI2000-Proceedings of the Sixth Pacific Rim International Conference on Artificial Intelligence, pages 252–263, Melbourne, Australia, 2000.
Ingrid Zukerman, Richard McConachy, and Kevin B. Korb. Bayesian reasoning in an abductive mechanism for argument generation and analysis. In AAAI98-Proceedings of the Fifteenth National Conference on Artificial Intelligence, pages 833–838, Madison,Wisconsin, 1998.
Ingrid Zukerman, Richard McConachy, Kevin B. Korb, and Deborah A. Pickett. Exploratory interaction with a Bayesian argumentation system. In IJCAI99-Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, pages 1294–1299, Stockholm, Sweden, 1999.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zukerman, I. (2001). An Integrated Approach for Generating Arguments and Rebuttals and Understanding Rejoinders. In: Bauer, M., Gmytrasiewicz, P.J., Vassileva, J. (eds) User Modeling 2001. UM 2001. Lecture Notes in Computer Science(), vol 2109. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44566-8_9
Download citation
DOI: https://doi.org/10.1007/3-540-44566-8_9
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-42325-6
Online ISBN: 978-3-540-44566-1
eBook Packages: Springer Book Archive