Математическое моделирование отношений агентов организационной системы
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Научный журнал Моделирование, оптимизация и информационные технологииThe scientific journal Modeling, Optimization and Information Technology
Online media
issn 2310-6018

Mathematical modeling of relations between agents of an organizational system

idRossikhina L.V., Betskov A.V.,  Makarov V.F.,  Kondratiev V.D. 

UDC 519.813.7
DOI: 10.26102/2310-6018/2024.47.4.001

  • Abstract
  • List of references
  • About authors

The article discusses the main types of relationships (conflict, assistance and independence) active agents, the manifestation of which is possible when they interact in the organizational system. The agent's activity is understood as the possibility of independent goal-setting, according to which he chooses actions and his unscrupulous behavior. To characterize active agents, the concept of a utility function is introduced, which determines the agent's choice of actions that allow its usefulness to be maximized, as a rule, this is profit. The mathematical formalization of the relations of active agents is given for the option of achieving the common goal of the organizational system, as well as taking into account the achievement of local goals by active agents. To describe the interaction of active agents in the process of achieving a common goal, a matrix of the state of the organizational system is proposed, which allows to identify the existing cores of conflict, independence and assistance between active agents. The elements of the matrix are quantitative estimates of the set of agent relationships. To determine quantitative estimates of the set of agent relationships, an algorithm based on the calculation of the relative discrepancy of utility functions has been developed, which allows determining the nature and degree of agent relationships. The author's classification of agent relations according to the degree of their manifestation is proposed. An example illustrating the practical implementation of the algorithm is given.

1. Wieviorka M. Social conflict. Current Sociology. 2013;61(5-6):696–713. https://doi.org/10.1177/0011392113499487

2. Liu J., Yu C., Li C., Han J. Cooperation or Conflict in Doctor-Patient Relationship? An Analysis From the Perspective of Evolutionary Game. IEEE Access. 2020;8:42898–42908. https://doi.org/10.1109/ACCESS.2020.2977385

3. Basile C., Cappadonia A., Lioy A. Algebraic Models to Detect and Solve Policy Conflicts. In: Computer Network Security: Fourth International Conference on Mathematical Methods, Models and Architectures for Computer Network Security, MMM-ACNS 2007: Proceedings, 13–15 September 2007, Saint Petersburg, Russia. Heidelberg: Springer Berlin; 2007. pp. 242–247. https://doi.org/10.1007/978-3-540-73986-9_20

4. Deja R. Conflict Analysis. In: Rough Set Methods and Applications: New Developments in Knowledge Discovery in Information Systems. Heidelberg: Physica; 2000. pp. 491–519. https://doi.org/10.1007/978-3-7908-1840-6_9

5. Ismaili S., Fidanova S. Application of Intuitionistic Fuzzy Sets for Conflict Resolution Modeling and Agent Based Simulation. International Journal BIOautomation. 2019;23(2):175–184. https://doi.org/10.7546/ijba.2019.23.2.000544

6. Skowron A., Ramanna S., Peters J.F. Conflict Analysis and Information Systems: A Rough Set Approach. In: Rough Sets and Knowledge Technology: First International Conference, RSKT 2006: Proceedings, 24–26 July 2006, Chongquing, China. Berlin, Heidelberg: Springer; 2006. pp. 233–240. https://doi.org/10.1007/11795131_34

7. Sysoev D.V. Methods for analyzing canonical correlation pleiades in conflict relationships in social groups. Information technologies in construction, social and economic systems. 2020;(4):9–14. (In Russ.).

8. Khvostov A.A., Zhuravlev A.A., Zhuravlev E.A., Sysoev D.V. Mathematical model of conflict dynamics based on Markov chain. Information technologies in construction, social and economic systems. 2019;(3 4):30–35. (In Russ.).

9. Burkov V.N., Enaleev A.K., Korgin N.A. Incentive Compatibility and Strategy-Proofness of Mechanisms of Organizational Behavior Control: Retrospective, State of the Art, and Prospects of Theoretical Research. Automation and Remote Control. 2021;82(7):1119–1143. https://doi.org/10.1134/S0005117921070018

10. Burkov V.N., Burkova I.V., Daulbaeva Z.M., Khodunov A.M. Mekhanizmy stimulirovaniya pri raznykh tipakh povedeniya agentov. In: Upravlenie razvitiem krupnomasshtabnykh sistem MLSD’2019: Materialy dvenadtsatoi mezhdunarodnoi konferentsii, 01–03 October 2019, Moscow, Russia. Moscow: V.A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences; 2019. P. 1184. (In Russ.). https://doi.org/10.25728/mlsd.2019.1.1184

11. Barkalov S.A., Kurochka P.N., Mailyan L.D., Serebryakova E.A. Optimizatsionnye modeli – instrument sistemnogo modelirovaniya. Moscow: OOO "Kredo"; 2023. 522 p. (In Russ.).

12. Sysoev V.V. Conflict. Cooperation. Independence. Moscow: Moscow Academy of Economics and Law; 1999. 151 p. (In Russ.).

Rossikhina Larisa Vitalievna
Doctor of Technical Sciences, Associate Professor
Email: rossihina_lv@mail.ru

Scopus | ORCID | eLibrary |

Academy of Management of the MIA of Russia

Moscow, Russia

Betskov Alexander Viktorovich
Doctor of Technical Sciences, Associate Professor

Academy of Management of the MIA of Russia

Moscow, Russia

Makarov Valery Fyodorovich
Doctor of Technical Sciences, Professor

Academy of Management of the MIA of Russia

Moscow, Russia

Kondratiev Victor Dmitrievich
Doctor of Technical Sciences, Professor

Moscow Automobile and Road Engineering State Technical University

Moscow, Russia

Keywords: agent, multiple relationships, conflict, assistance, independence, utility function, quantitative assessment of relationships, matrix of the state of the organizational system

For citation: Rossikhina L.V., Betskov A.V., Makarov V.F., Kondratiev V.D. Mathematical modeling of relations between agents of an organizational system. Modeling, Optimization and Information Technology. 2024;12(4). URL: https://moitvivt.ru/ru/journal/pdf?id=1661 DOI: 10.26102/2310-6018/2024.47.4.001 (In Russ).

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Full text in PDF

Received 13.09.2024

Revised 27.09.2024

Accepted 08.10.2024