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A Framework for Merging Possibilistic Knowledge Bases

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Intelligent Information and Database Systems (ACIIDS 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11432))

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Abstract

Knowledge base merging is one of active research fields with a large range of applications in Artificial Intelligence. Most of the works in this research field has a lot of restrictions such as in the centralized approach, drowning effect, it is difficult to apply to interactive systems such as multi-agent systems as well as omitting knowledge in the merging process. The purpose of this paper is to focus on the integration of possibilistic knowledge bases in the propositional sense in propositional language. The integration is done through the special possibility distribution of possibilistic knowledge bases. To solve that problem, we introduce a new powerful argumentation framework for merging knowledge bases. In order to model this argument, firstly, the source knowledge bases of each agent are ranked in order of priority and the merging of prior knowledge bases into a priority knowledge base and then infer the final knowledge. An axiomatic model, including a set of rational and intuitive postulates is interested and discussed so that the merging result of knowledge bases needs to be satisfied.

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Authors and Affiliations

  1. University of Engineering and Technology, Vietnam National University, Hanoi, Vietnam

    Thi Thanh Luu Le

  2. University of Finance and Accountancy, Tu Nghia, Quangngai, Vietnam

    Thi Thanh Luu Le

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  1. Thi Thanh Luu Le
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Correspondence to Thi Thanh Luu Le .

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Editors and Affiliations

  1. Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Ngoc Thanh Nguyen

  2. Bina Nusantara University, Jakarta, Indonesia

    Ford Lumban Gaol

  3. National University of Kaohsiung, Kaohsiung, Taiwan

    Tzung-Pei Hong

  4. Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

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Le, T.T.L. (2019). A Framework for Merging Possibilistic Knowledge Bases. In: Nguyen, N., Gaol, F., Hong, TP., Trawiński, B. (eds) Intelligent Information and Database Systems. ACIIDS 2019. Lecture Notes in Computer Science(), vol 11432. Springer, Cham. https://doi.org/10.1007/978-3-030-14802-7_6

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  • DOI: https://doi.org/10.1007/978-3-030-14802-7_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-14801-0

  • Online ISBN: 978-3-030-14802-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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