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Title
Some inconsistency measures and method for restoring consistency in probabilistic knowledge bases
Speaker
Nguyen Van Tham, UET, VNU
Time: 15:30, Tuesday, April 9, 2019
Venue: E3-707, 144 Xuan Thuy, Cau Giay, Hanoi
ABSTRACT
Ensuring consistency of knowledge systems is always one of the essential requirements because, without it, most of these systems become useless. Because of the importance, many studies have involved the restoration of consistency in knowledge systems. However, these approaches are only implemented on knowledge systems that are represented by logic or probabilistic logic, thus when we apply them to probabilistic knowledge systems, there are many inadequacies. In order to overcome these drawbacks, in this paper, we put forward a new model for restoring the consistency of a probabilistic knowledge base by focusing on changing the probabilities in this knowledge base via several inconsistency measures. To this end, a set of inconsistency measures is presented and a family of consistency restoring operators for probabilistic knowledge bases are introduced. Next, an axiomatic model consists of a set of axioms is built to characterize the desirable properties of the consistency of restoring operators. Finally, the properties of each consistency restoring operator in the introduced family are investigated and discussed.