A Bayesian approach to automating argumentation

Authors:
Richard McConachy;Kevin B. Korb;Ingrid Zukerman
Affiliations:
Monash University, Clayton, Victoria, Australia;Monash University, Clayton, Victoria, Australia;Monash University, Clayton, Victoria, Australia
Venue:
NeMLaP3/CoNLL '98 Proceedings of the Joint Conferences on New Methods in Language Processing and Computational Natural Language Learning
Year:
1998

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Abstract

Our argumentation system NAG uses Bayesian networks in a user model and in a normative model to assemble and assess nice arguments, that is arguments which balance persuasiveness with normative correctness. Attentional focus is simulated in both models to select relevant subnetworks for Bayesian propagation. Bayesian propagation in the user model is modified to represent some human cognitive weaknesses. The subnetworks are expanded in an iterative abductive process until argumentative goals are achieved in both models, when the argument is presented to the user.