THE ELECTRONIC SCIENTIFIC JOURNAL "YOUNG SCIENCE OF SIBERIA"

VERIFICATION AND SEARCH OF CONTRADICTIONS IN KNOWLEDGE BASES OF THE INTELLIGENT SYSTEMS

Authors: 
M.S. Nitezhuk
Receipt date: 
23.11.2018
Bibliographic description of the article: 

Nitezhuk M.S. Verifikaciya i poisk protivorechij v bazah znanij intellektual'nykh sistem [Verification and search of contradictions in knowledge bases of the intelligent systems]. Molodaya nauka Sibiri: ehlektronnyj nauchnyj zhurnal [Young science of Siberia: electronic scientific journal], 2018, no. 2. [Accessed 17/12/18]

Section: 
5. COMPUTER SCIENCE
Year: 
2018
Journal number: 
2(2) 2018
УДК: 
004.82
Article File: 
PDF icon nitezhukverifikaciya_bz_iis.pdf
Abstract: 

The article discusses the methods and approaches to the verification of knowledge bases of intelligent information systems on the example of the production model of knowledge. Both expert systems knowledge bases and other information storages are considered. It is noted that the typical mistakes in the development of knowledge bases are their inconsistency, incompleteness, redundancy. Means of struggle with these problems are considered: development of specialized programs and algorithms, ontological modeling for the detailed description of semantics of a subject area and other. The assumption is made about the purposefulness of using non-classical logical calculi for the verification of knowledge bases, capable of processing information with a significant degree of incompleteness and inconsistency: logic with vector semantics (VTF-logic as their special case) and neutrosophic Smarandake logic

Keywords: 
artificial intelligence
expert system
knowledge base
rule-based model
verification
contradictions
logic with vector semantic
List of references: 
  1. Gaskarov D.V. Intellektualnyye informatsionnyye sistemy. Ucheb. dlya vuzov. [Intelligent information systems: textbook for high schools] M.: vysh. shk.. 2003. 431 s. (in Russian).
  2. Sovetov B.Ya.. Tsekhanovskiy V.V.. Chertovskiy V.D. Intellektualnyye sistemy i tekhnologii: uchebnik dlya stud. uchrezhdeniy vysh. prof. obrazovaniya. [Intelligent  Systems: textbook for students of high professional schools] M.: Izdatelskiy tsentr «Akademiya». 2013. 320 s. (in Russian).
  3. Gavrilova T.A.. Khoroshevskiy V.F. Bazy znaniy intellektualnykh system [Knowledge Bases of the Intelligent Systems]. SPb: Piter. 2000. 384 s. (in Russian)
  4. Makarenko S.I. Intellektualnyye informatsionnyye sistemy: ucheb. posobiye. [Intelligent information systems: textbook]. Stavropol: SF MGTU im M.A. Sholokhova. 2009. 206 s. (in Russian).
  5. Arshinskiy L.V. Teoreticheskiye osnovy iskusstvennogo intellekta: uchebnoye posobiye [Theoretical foundations of artificial intelligence: textbook]. Irkutsk: IrGUPS. 2016. 142 s. (in Russian).
  6. Rybina G.V. Osnovy postroyeniya intellektualnykh informatsionnykh sistem: ucheb. posob. [Fundamentals of building intelligent information systems: textbook] M.: Finansy i statistika. INFRA-M. 2010. 432 s. (in Russian)
  7. Marcot B. Testing your knowledge base // AI Expert. August. 1987. pp 43-47.
  8. Dolinina O.N. Klassifikaciya oshibok v bazah znanij ehkspertnyh sistem [Classification of errors in knowledge bases of expert systems] // Vestnik SGTU. 2010. № 4 (50). Vyp. 2. S. 125–130. (in Russian)
  9. Andreyev A.M.. Berezkin D.V.. Simakov K.V. Osobennosti proyektirovaniya modeli i ontologii predmetnoy oblasti dlya poiska protivorechiy v pravovykh elektronnykh bibliotekakh [Design features of the model and ontology of the subject area for the search of contradictions in legal electronic libraries] – http://inteltec.ru/publish/articles/textan/RCDL2004.shtml (in Russian).
  10. Pronina I.G. Metody i instrumentalnyye sredstva podderzhki produktsionnykh baz znaniy, soderzhashchikh pravila s intervalnymi znacheniyami kharakteristik v predikatakh: dissertatsiya ... kandidata tekhnicheskikh nauk: 05.13.11 [Methods and tools for support of production knowledge bases containing rules with interval values of characteristics in predicates: dissertation ... candidate of technical sciences]. M., 1994. 160 s. (in Russian).
  11. Preece A.D., Shinghal R., Batarekh A. Verifying expert systems: a logical framework and a practical tool // Expert systems with applications. 1992. Vol. 5. P. 421–436.
  12. Proskuryakov D.P. Upravleniye razresheniyem konfliktov v produktsionnykh ekspertnykh sistemakh [Managing conflict resolution in rule-based expert systems] // Vestnik Irkutskogo gosudarstvennogo tekhnicheskogo universiteta. 2015. № 8. S. 47-51. (in Russian).
  13. Pospelova L.Ya.. Chukanova O.V. Poisk protivorechiy v produktsionnykh bazakh zna-niy [The search for contradictions in the rule-based knowledge bases]. – http://www.vmest.ru/nuda/poisk-protivorechij-v-produkcionnih-bazah-znani.... (in Russian).
  14. Post E.L. Formal Reductions of the General Combination Decision Problem // American Journal of Mathematics. Vol. 65. 1943. pp. 197-215.
  15. Tepandi J. Comparison of Expert System Verification Criteria: Redundancy // Proc. ECAI 90 Conf. Stockholm, 1990. pp 49-62.
  16. Tekhnologiya baz znaniy [Knowledge base technology]. – http://konesh.ru/lekciya-11-tehnologiya-baz-znanij.html. (in Russian).
  17. Alchourron C., Gardenfors P., Makinson D. On the logic of theory change: partial meet contraction and revision functions // Journal of Symbolic Logic. 1985. Vol. 50, No. 4. P. 510-530.
  18. Flouris G., Huang Z., Pan J.Z., Plexousakis D., and Wache H. Inconsistencies, Negations and Changes in Ontologies // Proceedings of the 21st  National Conference on Artificial Intelligence AAI-06. 2006. P. 1295-1300.
  19. Pospelova L.Ya. Mera soglasovannosti nechetkoy bazy znaniy i metodika eye otsenki [Measure of consistency of fuzzy knowledge base and methods of its evaluation] // XII Vserossiyskoye soveshchaniye po problemam upravleniya VSPU-2014. Moskva. 16-19 iyunya 2014 g. – S. 4010-4017. – http://docplayer.ru/45831239-Mera-soglasovannosti-nechetkoy-bazy-znaniy-... (in Russian).
  20. Ivanov A.S. Matematicheskiye modeli i algoritmy funktsionirovaniya produktsionnykh baz znaniy: dissertatsiya ... kandidata fiziko-matematicheskikh nauk: 05.13.18 [Mathematical models and algorithms of production knowledge bases functioning: dissertation ... candidate of physical and mathematical Sciences]. Saratov. 2008. - 117 s. (in Russian).
  21. Vasilyev N.A. O chastnykh suzhdeniyakh, o treugolnike protivopolozhnostey, o zakone isklyuchennogo chetvertogo [On particular judgments, on the triangle of opposites, on the law of the excluded fourth]. Kazan. 1910. (in Russian).
  22. Vasilyev N.A. Voobrazhayemaya logika. Izbrannyye Trudy [Imaginary logic. Selected works]. M.: Nauka. 1989. 264 s. (in Russian).
  23. Tishkov A.V. et al. Obnaruzheniye i ustraneniye protivorechiy v spetsifikatsiyakh slozhnykh system [Detection and elimination of contradictions in the specifications of complex systems]. – http://skachate.ru/informatika/8252/index.html (in Russian).
  24. Vyyavleniye protivorechiy [Identification of contradictions]. – https://studfiles.net/preview/964885/page:13 (in Russian).
  25. Davis R. Use of meta level knowledge in the construction and maintenance of large knowledge bases: Ph.D. dissertation, Computer Science Departmenr, Stanford University, Stanford, California, 1976, 197 p.
  26. Dolina O.S. Razrabotka metoda testirovaniya produktsionnykh baz znaniy ekspertnykh sistem s uchetom oshibok tipa «zabyvaniye ob isklyuchenii»: dissertatsiya … kandidata tekhnicheskikh nauk: 05.13.14 [Development of the method of testing the production knowledge bases of expert systems taking into account errors such as "forgetting about exclusion": dissertation ... candidate of technical Sciences]. Saratov. 1999. 174 s. (in Russian).
  27. Proskuryakov D.P. Poisk protivorechij s pomoshch'yu strategii upravleniya produkciyami na osnove ontologii predmetnoj oblasti [The search for contradictions with management strategy of the production rules on the basis of domain ontology]// Trudy XIX Bajkal'skoj Vserossijskoj konferencii «Informacionnye i matematicheskie tekhnologii v nauke i upravlenii». CH. III. Irkutsk: ISEHM SO RAN, 2014. S. 166–170.(in Russian)
  28. Yalovets A.L. Predstavleniye i obrabotka znaniy s tochki zreniya matematicheskogo modelirovaniya. Problemy i resheniya [Knowledge representation and processing in terms of mathematical modeling. Problems and solutions]. Kiev. Naukova Dumka, 2011, 339 с. (in Russian)
  29. Proskuryakov D.P. Integratsiya ontologicheskogo modelirovaniya i rassuzhdeniy po pretsedentam dlya obrabotki konteksta v issledovaniyakh energeticheskoy bezopasnosti [Integration of ontological modeling and reasoning in the precedents for the processing of context in studies of energy security] // Vestnik Irkutskogo gosudarstvennogo tekhnicheskogo universiteta. 2017. vol. 21 N 4(123). pp. 90-99. (in Russian)
  30. Arshinskiy V.L.. Proskuryakov D.P. Primeneniye ontologiy i rassuzhdeniya po pretsedentam dlya obrabotki konteksta v sobytiynom modelirovanii v issledovaniyakh energetiki [Application of ontologies and precedent reasoning for context processing in event modeling in energy research] // Sovremennyye tekhnologii. Sistemnyy analiz. Modelirovaniye. 2016. № 4 (52). pp. 94–100. (in Russian)
  31. Plaza E., Arcos J.L. Constructive adaptation // Advances in case-based reasoning. Springer Verlag. 2002. Vol. 2416. pp. 306–320.
  32. Arshinskii L.V. Substantial and formal deductions in logics with vector semantics // Automation and remote control, 2007. Vol. 68, № 1. pp. 139-148.
  33. Arshinskiy L.V. Mnogoznachnyye logiki s vektornoy semantikoy [Multivalued logic with vector semantics]. Dep. v VINITI 13.02.03 №281-V2003. 46 p. (in Russian)
  34. Arshinskiy L.V. Issledovaniye i razrabotka matematicheskikh modeley obrabotki nepolnykh i protivorechivykh dannykh na osnove logik s vektornoy semantikoy: avtoreferat dissertatsii … doktora tekhnicheskikh nauk: 05.13.18.[Research and development of mathematical models of incomplete and contradictory data processing based on logic with vector semantics: dissertation abstract ... doctor of technical Sciences] Irkutsk. 2007. 40 p. (in Russian)
  35.  Smarandache F. Neutrosophy: Neutrosophic Probability. Set and Logic. American Re-search Press. Rehoboth. 1998. 105 p.
  36. Smarandache, F. An Introduction to Neutrosophy, Neutrosophic Logic, Neutrosophic Set, and Neutrosophic Probability and Statistics // Proc. of the First International Conference on Neutrosophy, Neutrosophic Logic, Neutrosophic Set, Neutrosophic Probability and Statistics. University of New Mexico-Gallup, 1-3 December 2001. Phoenix: Xiquan, 2001. P. 5-21.
  37. Smarandake F. Sushchnost neytrosofii [The essence of neutrosophy]. Hexis Publishers. Feniks. Arizona. 2006. 33 p. (in Russian)
  38. Arshinskiy L.V. Primeneniye vektornogo formalizma v logike i logiko-matematicheskom modelirovanii [Application of vector formalism in logic and logical-mathematical modeling] // Ontologiya proyektirovaniya. 2016. Vol. 6. N4 (22). pp. 436-451.
  39. Arshinskiy L.V. Metody obrabotki nestrogikh vyskazyvaniy [Methods of processing of non-strict proposition]. Irkutsk: East-Siberian Institute of MIA of Russia. 1998. 40 p. (in Russian)