Advertisement

Intellectual Monitoring Systems in a Complex Multi-agent System

  • Madina Fozilova
  • Otabek Ismoilov
Conference paper

Abstract

Carrying out full-scale studies is practically impossible, in connection with which there is a wide attraction of modern mathematical models, numerical methods and information technologies, based on methods of artificial intelligence. In this regard, the issues of creating a new class of models that combine the features and properties of uncertainty and their software implementation are very relevant. The analysis of the perspective of the technology of intelligent monitoring systems has been conducted in the work, as intellectualization is the main direction of development of modern technologies, and the property of intellectuality should be inherent in all the latest information management systems. Various strategies for intellectualization of monitoring aim at implementing intellectual information support for decision-makers using monitoring tools. Such support can be realized by building fuzzy linguistic databases/knowledge together with fuzzy inference subsystems, and information for decision making can be displayed on the automated workplace of the decision maker.

Keywords

Intellectual intelligence Hybrid intelligent systems Neuro-fuzzy models Evolutionary algorithms Multi-agent intellectual system 

References

  1. 1.
    Bordini Rafael H (2005) In: Bordini RH, Dastani M, Dix J, Seghrouchni AEF (eds) Multi-agent programming: languages, platforms and applications. Springer, Boston. 296 pzbMATHGoogle Scholar
  2. 2.
    Lin Hong (2007) Architectural design of multi-agent systems: technologies and techniques. Premier reference series. Hong Lin, IGI Global, 421 pGoogle Scholar
  3. 3.
    Shamma Jeff (2008) Cooperative control of distributed multi-agent systems. Wiley, Chichester, 437 pGoogle Scholar
  4. 4.
    Gavrilova TA, Khoroshevsky VF (2000) Bases of knowledge of intellectual systems. St. Petersburg, Peter, 384 pGoogle Scholar
  5. 5.
    Zade LA (2001) The role of soft computing and fuzzy logic in understanding, designing and developing information intellectual systems. News Artif Intell 2–3:7–11Google Scholar
  6. 6.
    Mukhamedieva D.T. (2015) Multiagent decision-making system. In: Proceedings of the international scientific and technical conference “Radioelectronics, information and telecommunication technologies: problems and development”. Tashkent, pp 38–41Google Scholar
  7. 7.
    Fazilova M, Muhamediyeva DK (2016) Multi-agent system for assessing the status of weakly formalized systems. BEST Int J Manag Inf Technol Eng 4(7):47–54. India. ISSN (Print): 2348-0513; ISSN (Online): 2454-471X; Impact Factor (JCC): 1.5429; Index Copernicus: 3.0Google Scholar
  8. 8.
    Fazilova MM, Mukhamedieva DK (2016) Approaches to the construction of a multi-agent intellectual system for assessing the state of weakly formalized processes. In: Proceedings of the reports of the republican scientific and technical conference “Current state and prospects of application of information technologies in management”, 5–6 September, pp 484–487. LivesGoogle Scholar
  9. 9.
    Fazilova MM, Mukhamedieva DK(2016) Multiagent system for assessing the state of weakly formalized objects. In: Proceedings of the reports of the republican scientific and technical conference “Current state and perspectives of application of information technologies in management”, 5–6 September, pp 487–491. LivesGoogle Scholar
  10. 10.
    Fozilova M, Mukhamediyeva DK (2016) Constructing a multi-agent intellectual system for assessing the state of weakly formalized processes. Int Sci Tech J Chem Technol Cont Manage 4:86–91. TashkentGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Madina Fozilova
    • 1
  • Otabek Ismoilov
    • 1
  1. 1.Scientific and Innovation Center of Information and Communication TechnologiesTashkentUzbekistan

Personalised recommendations