Pr$\mathcal{SH}$: A Belief Description Logic

  • Authors:

  • Tao Jia;Wen Zhao;Lifu Wang

  • Affiliations:

  • School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China;School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China;School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China

  • Venue:
  • KES-AMSTA '07 Proceedings of the 1st KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications
  • Year:
  • 2007

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Abstract

Some research has been done on probabilistic extension of description logics such as P-CLASSIC and P-$\mathcal {SHOQ}$ which focus on the statistical information. For example, in those kind of probabilistic DL, we can express such kind of uncertainty that the probability a randomlychosen individual in concept Cis also in concept Dis 90 percent. This kind of statistical knowledge is certain which means the author of this statement is sure about it. In this paper, we will describe a new kind of probabilistic description logic Pr$\mathcal{SH}$ which could let user express the uncertain knowledge(i.e. degrees of belief). For example, if the user is not sure about that concept Cis subsumed by concept D, he could describe it with Pr$\mathcal{SH}$ such as the probability that concept Cis subsumed by concept Dis 90 percent.Furthermore, user could make use of the uncertain knowledge to infer some implicit knowledge by the extension of tableau-algorithmof $\mathcal {SH}$ which will be also introduced in this paper.