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Journal Neurocomputers №9 for 2016 г.
Article in number:
The structure of the hybrid intelligent information system based on metagraphs
Keywords: hybrid intelligent information system (HIIS) conscious and subconscious of information system multi-agent ap-proach holonic organization metagraph neural networks
Authors:
V.M. Chernenkiy - Dr.Sc. (Eng.), Professor, Head of Information Processing and Control Systems Department, Bauman Moscow State Technical University. E-mail: iu5vmch@rambler.ru V.I. Terekhov - Ph.D. (Eng.), Associate Professor, Information Processing and Control Systems Department, Bauman Moscow State Technical University). E-mail: terekchow@bmstu.ru Yu.E. Gapanyuk - Ph.D. (Eng.), Associate Professor, Information Processing and Control Systems Depart-ment, Bauman Moscow State Technical University). E-mail: gapyu@bmstu.ru
Abstract:
The article is devoted to the structure of the hybrid intelligent information system (HIIS) based on multi-agent approach. Ge-neralized structure of HIIS based on modules of consciousness and subconsciousness is discussed. Special cases of the structure of HIIS for different variants of information systems are given. For HIIS implementation usage of multi-agent approach based on holonic organization is proposed. Requirements for agent of holonic multi-agent system are addressed. To describe the structure of the agent is proposed to use the metagraph. The formal model of metagraph is discussed. The concept of information element of a metagraph (IEM) is introduced. Basic operations on metagraphs based on IEM are discussed. Description of holonic multi-agent system in statics based on metagraph is given. For description in statics usage of agents-functions, metagraph agents and container agents is proposed. Description of holonic multi-agent system in dynamics based on metagraph is given. For description in dynamics usage of dynamic metagraph agents is proposed.
Pages: 3-13
References

 

  1. Kolesnikov A.V. Gibridnye intellektualnye sistemy. Teorija i tekhnologija razrabotki. SPb: SPbGTU. 2001.
  2. Kolesnikov A.V., Kirikov I.A., Listopad S.V. Gibridnye intellektualnye sistemy s samoorganizaciejj: koordinacija, soglasovannost, spor. M.: IPI RAN. 2014. 189 s.
  3. Prikladnye intellektualnye sistemy, osnovannye na mjagkikh vychislenijakh / Pod red. N.G. JArushkinojj. Uljanovsk: UlGTU. 2004. 139 s.
  4. Michal Bali. Dools JBoss Rules 5.0 Developer-s Guide. PACKT publishing, 2013. 338 p.
  5. Dzharratano D., Rajjli G. EHkspertnye sistemy: principy razrabotki i programmirovanie. Izd. 4-e. M.: ID «Viljams». 2006. 1152 s.
  6. Tarasov V.B. Ot mnogoagentnykh sistem k intellektualnym organizacijam: filosofija, psikhologija, informatika. M.: EHditorial URSS. 2002. 352 s.
  7. Xiao X., Zhang H., Hasegawa O. Density Estimation Method Based on Self-Organizing Incremental Neural Network and Error Estimation // Proceedings of the Neural Information Processing: 20th International Conference, ICONIP 2013. Daegu, Korea. 2013. R. 43-50.
  8. Pugh J.K., Stanley K.O. Evolving Multimodal Controllers with HyperNEAT. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2013). New York, NY: ACM, 2013. 8 p.
  9. Samokhvalov EH.N., Revunkov G.I., Gapanjuk JU.E. Ispolzovanie metagrafov dlja opisanija semantiki i pragmatiki informacionnykh sistem // Vestnik MGTU im. N.EH. Baumana. Ser. Priborostroenie. 2015. Vyp. №1.
  10. CHernenkijj V.M. Algoritmicheskaja model opisanija diskretnogo processa funkcionirovanija sistemy // technomag.edu.ru:Nauka i Obrazovanie: ehlektronnoe nauchno-tekhnicheskoe izdanie. 2011. Vyp. 12. URL http://technomag.edu.ru/doc/292997.html.
  11. CHechkin A.V. Intellektualnaja informacionnaja sistema na osnove radikalnogo modelirovanija kak instrumentalnoe sredstvo obespechenija kompleksnogo razvitija // Nejjrokompjutery: razrabotka, primenenie. 2015. Vyp. № 5. S. 7-13.