A tableau algorithm for paraconsistent and nonmonotonic reasoning in description logic-based system
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| Title | A tableau algorithm for paraconsistent and nonmonotonic reasoning in description logic-based system |
|---|---|
| Author | Lin, Zuoquan; Zhang, Xiaowang; Wang, Kewen |
| Publication Title | Proceedings 13th Asia-PacificWeb Conference: Web Technologies and Applications |
| Editor | Xiaoyong Du, Wenfei Fan, Jianmin Wang, Zhiyong Peng, Mohamed A. Sharaf |
| Year Published | 2011 |
| Place of publication | United Kingdom |
| Publisher | Springer |
| Abstract | This paper proposes a paraconsistent and nonmonotonic extension of description logic by planting a nonmonotonic mechanism called \emph{minimal inconsistency} in paradoxical description logics, which is a paraconsistent version of description logics. A precedence relation between two paradoxical models of knowledge bases is firstly introduced to obtain minimally paradoxical models by filtering those models which contain more inconsistencies than others. A new entailment relationship between a KB and an axiom characterized by minimal paradoxical models is applied to characterize the semantics of a paraconsistent and nonmonotonic description logic. An important advantage of our adaptation is simultaneously overtaking proverbial shortcomings of existing two kinds extensions of description logics: the weak inference power of paraconsistent description logics and the incapacity of nonmonotonic description logics in handling inconsistencies. Moreover, our paraconsistent and nonmonotonic extension not only preserves the syntax of description logic but also maintains the decidability of basic reasoning problems in description logics. Finally, we develop a sound and complete tableau algorithm for instance checking with the minimally paradoxical semantics. |
| Peer Reviewed | Yes |
| Published | Yes |
| Alternative URI | http://dx.doi.org/10.1007/978-3-642-20291-9_36 |
| Copyright Statement | Copyright 2011 Springer Berlin / Heidelberg. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. The original publication is available at www.springerlink.com |
| ISBN | 9783642202902 |
| Conference name | APWeb 2011 |
| Location | Beijing, China |
| Date From | 2011-04-18 |
| Date To | 2011-04-20 |
| URI | http://hdl.handle.net/10072/42801 |
| Date Accessioned | 2011-09-28 |
| Date Available | 2012-10-18T04:49:35Z |
| Language | en_US |
| Research Centre | Institute for Integrated and Intelligent Systems |
| Faculty | Faculty of Science, Environment, Engineering and Technology |
| Subject | Artificial Intelligence and Image Processing |
| Publication Type | Conference Publications (Full Written Paper - Refereed) |
| Publication Type Code | e1 |
Please use this identifier to cite this record: http://hdl.handle.net/10072/42801
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