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A Knowledge Representation in Possible World

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Computational Intelligence and Intelligent Systems (ISICA 2012)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 316))

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Abstract

In order to represent the knowledge model of the combination of time and actions in a possible world,this article proposes a knowledge representation(KR) method which is based on first order logic and its semantic can be interpreted by production rules. First,we discuss the basic theory of knowledge representation(KR), and next,we construct a meta language through which semantic can be explained by the rules of semantic interpretation and predicates, and then,by the meta language and its semantic we describe the concepts in the possible world. At last,we use experiments in the possible world to demonstrate the effectiveness of the presented method.

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Author information

Authors and Affiliations

  1. Kunming University of Science and Technology, Kunming City, P.R. China

    Yangxin Ou, Ping Zou & Chunyan Shuai

  2. Yunnan Key Lab of Computer Technology Application, Kunming City, P.R. China

    Yangxin Ou

Authors
  1. Yangxin Ou
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  2. Ping Zou
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  3. Chunyan Shuai
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Editor information

Editors and Affiliations

  1. School of Computer Science, China University of Geosciences, Wuhan, China

    Zhenhua Li  & Xiang Li  & 

  2. School of Computer Science and Engineering, The University of Aizu, Aizu, Japan

    Yong Liu

  3. School of Computer Science, China University of Geosciences, 430074, Wuhan, China

    Zhihua Cai

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© 2012 Springer-Verlag Berlin Heidelberg

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Ou, Y., Zou, P., Shuai, C. (2012). A Knowledge Representation in Possible World. In: Li, Z., Li, X., Liu, Y., Cai, Z. (eds) Computational Intelligence and Intelligent Systems. ISICA 2012. Communications in Computer and Information Science, vol 316. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34289-9_57

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  • DOI: https://doi.org/10.1007/978-3-642-34289-9_57

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34288-2

  • Online ISBN: 978-3-642-34289-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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