Belief merging is one of active research fields with a large range of applications in Artificial Intelligence. Most of the work in this research field is in the centralized approach, however, it is difficult to apply to interactive systems such as multi-agent systems. In this paper, we introduce a new argumentation framework for belief merging. To this end, a constructive model to merge possiblistic belief bases built based on the famous general argumentation framework is proposed. An axiomatic model, including a set of rational and intuitive postulates to characterize the merging result is introduced and several logical properties are mentioned and discussed.
CITATION STYLE
Nguyen, T. H. K., Tran, T. H., Van Nguyen, T., & Le, T. T. L. (2017). Merging possibilistic belief bases by argumentation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10191 LNAI, pp. 24–34). Springer Verlag. https://doi.org/10.1007/978-3-319-54472-4_3
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