МЕТОДОЛОГИЯ МОДЕЛИРОВАНИЯ ПРОСТРАНСТВЕННЫХ ИНТЕЛЛЕКТУАЛЬНЫХ АГЕНТОВ НА ПРИМЕРЕ С#
Работая с нашим сайтом, вы даете свое согласие на использование файлов cookie. Это необходимо для нормального функционирования сайта, показа целевой рекламы и анализа трафика. Статистика использования сайта отправляется в «Яндекс» и «Google»
Научный журнал Моделирование, оптимизация и информационные технологииThe scientific journal Modeling, Optimization and Information Technology
Online media
issn 2310-6018

METHODOLOGY OF SIMULATION OF SPATIAL INTELLIGENT AGENTS AS EXAMPLE ON C #

Burilina M.A.  

UDC 519.876.5
DOI:

  • Abstract
  • List of references
  • About authors

It remains unquestionable that the development of programming languages, the introduction of various digital platforms and navigation to improve the visualized models, in particular agent-oriented, will lead to the need to create a single programming language for supercomputers. This work can be useful in developing a model involving intelligent agents that have a GIS-binding to the map. This model was built by using the C # programming language; witch includes the construction of decentralized agent-oriented social systems. The paper describes the need for a parallelization process for complex agent-based models. The article has been prepared with the support of the Russian Science Foundation, Grant No14- 18-01968.

1. «Intelligent Agents: Theory and Practice. M Wooldridge, NR Jennings» - The knowledge engineering review, Vol. 10:2, 1995, p. 115-152.

2. Bakhtizin A.R. Agent-oriented models of the economy. Moscow: Economics, 2008. 279 p.

3. Parsopoulos, KE «Recent Approaches to Global Optimization Problems Through Particle Swarm Optimization». Natural Computing 1 (2-3): pp. 235–306. 2002. DOI:10.1023/A:1016568309421.

4. Burilina M.A., Akhmadeev B.A. Analysis of the diversity of architectures and methods for modeling decentralized systems based on the agent-based approach. Creative Economy No. 7/2016 DOI: 10.18334 / ce.10.7.35364

5. Weber Sh., Davidov D., Savvateev A. Institutions of decision making // Issues of Economics, No. 6, June 2017, pp. 45-57.

6. V.L. Makarov, A.R. Bakhtizin, E.D. Sushko, A.F. Ageeva Artificial society and real demographic processes, Economics and mathematical methods, publishing house Science, Volume 53, №1, p.3-18.

7. A.F. Ageeva Large-scale agent-oriented models and their technical implementation on supercomputers. Modeling, optimization and information technology. Scientific journal №3 (18) http://moit.vivt.ru/ 2017 UDC 519.876.5.

8. Simulation of an Organization of Spatial Intelligent Agents in the Visual C#.NET Framework. Reza Nourjou and Michinori Hatayama International Journal of Computer Theory and Engineering, Vol. 6, No. 5, October 2014 DOI: 10.7763/IJCTE. 2014.V6.903 p.426-431

9. [Electronic resource] URL: https://habrahabr.ru/post/66562/ (date of the address: 9/20/2017).

10. Fattakhov M.R. Agent-oriented model of social and economic development of Moscow. Economics and Mathematical Methods, 2013, Vol. 49, No. 2, p. 30-43.

Burilina Maria Alekseevna

Central Economics and Mathematics Institute of RAS

Moscow, Russian Federation

Keywords: agent-based models, artificial society, agent behavior, agent architecture, parallelization, mathematical modeling of agent behavior, intellectual agents

For citation: Burilina M.A. METHODOLOGY OF SIMULATION OF SPATIAL INTELLIGENT AGENTS AS EXAMPLE ON C #. Modeling, Optimization and Information Technology. 2017;5(3). Available from: https://moit.vivt.ru/wp-content/uploads/2017/08/Burilina_3_1_17.pdf DOI: (In Russ).

499

Full text in PDF