Approximation reasoning models based on random variables sequence

  • Authors:
  • Jialu Zhang;Xia Wu;Xiaoling Liu

  • Affiliations:
  • Department of Mathematics, Xiangnan University, Chenzhou, Hunan, China;Department of Mathematics, Xiangnan University, Chenzhou, Hunan, China;Department of Computer Science, Xiangnan University, Chenzhou, Hunan, China

  • Venue:
  • Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
  • Year:
  • 2014

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Abstract

In this paper, we introduce the concept of random truth degree of an abstract proposition, which is a common generalization of various concepts of truth degree existing in literature, and prove that the set of random truth degree of all propositions has no isolated points in the real unit interval I = [0, 1]. We define random resemblance degree and random logic pseudo-metric among two propositions by means of random truth degrees, and prove that the random logic pseudo-metric space has no isolated points. By virtue of integral convergence theorem in probability theory we give a limit theorem of random truth degrees, which shows the connection of various truth degrees existing in literature. As an application we propose two diverse approximate reasoning models in random logic pseudo-metric space.