Approximate declarative semantics for rule base anomalies |
| |
| Affiliation: | 1. Department of Computer Science, California State University, Sacramento, CA 95819-6021, USA;2. Department of Computer Science, Naval Postgraduate School, Monterey, CA 93943, USA;1. College of Computer Science and Information Engineer, Harbin Normal University, Harbin, Heilongjiang Province, 150025, China;2. Department of Computer Science, University of Regina, Regina, Saskatchewan, S4S 0A2, Canada;1. School of Economics and Management, Fuzhou University, Fuzhou 350116,China;2. School of Management and Economics, University of Electronic Science and Technology of China, Chengdu 611731, China;3. Odette School of Business, University of Windsor, Windsor, Ontario N9B 3P4 Canada;4. School of Transportation and Civil Engineering, Fujian Agriculture and Forestry University, Fuzhou 350002, China;1. The Norwegian Structural Biology Centre (NorStruct), Department of Chemistry, Faculty of Science and Technology, UiT The Arctic University of Norway, N-9037 Tromsø, Norway;2. Department of Chemistry, Faculty of Science and Technology, UiT The Arctic University of Norway, N-9037 Tromsø, Norway;3. Norwegian National Advisory Unit on Detection of Antimicrobial Resistance, Department of Microbiology and Infection Control, University Hospital of North Norway, N-9038 Tromsø, Norway;4. Department of Pharmacy, UiT The Arctic University of Norway, N-9037 Tromsø, Norway |
| |
| Abstract: | Despite the fact that there has been a surge of publications in verification and validation of knowledge-based systems and expert systems in the past decade, there are still gaps in the study of verification and validation (V&V) of expert systems, not the least of which is the lack of appropriate semantics for expert system programming languages. Without a semantics, it is hard to formally define and analyze knowledge base anomalies such as inconsistency and redundancy, and it is hard to assess the effectiveness of V&V tools, methods and techniques that have been developed or proposed. In this paper, we develop an approximate declarative semantics for rule-based knowledge bases and provide a formal definition and analysis of knowledge base inconsistency, redundancy, circularity and incompleteness in terms of theories in the first order predicate logic. In the paper, we offer classifications of commonly found cases of inconsistency, redundancy, circularity and incompleteness. Finally, general guidelines on how to remedy knowledge base anomalies are given. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
