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ISSN 2587-814X (print),
ISSN 2587-8158 (online)

Russian version: ISSN 1998-0663 (print),
ISSN 2587-8166 (online)

Armen Beklaryan 1,2, Andranik Akopov3
  • 1 National Research University Higher School of Economics, 20 Myasnitskaya Str., Moscow, 101000, Russian Federation
  • 2 Central Economics and Mathematics Institute, Russian Academy of Sciences, 47, Nachimovky Prospect, Moscow, 117418, Russia
  • 3 Central Economic and Mathematical Institute, Russian Academy of Sciences, Moscow, Russia

Simulation of human crowd behavior based on intellectual dynamics of interacting agents

2015. No. 1 (31). P. 69–77 [issue contents]

Armen L. Beklaryan - Lecturer, Department of Business Analytics, Faculty of Business Informatics, National Research University Higher School of Economics
Address: 20, Myasnitskaya street, Moscow, 101000, Russian Federation.
E-mail: abeklaryan@hse.ru

Andranik S. Akopov - Professor, Department of Business Analytics, Faculty of Business Informatics, National Research University Higher School of Economics
Address: 20, Myasnitskaya street, Moscow, 101000, Russian Federation.
E-mail: aakopov@hse.ru

      This paper elaborates a phenomenological approach to simulation of human crowd behavior. We consider a continuous stochastic agent-based model of human behavior in a confined space with a given geometry by using refinements of both an agent status and agent’s decision-making system, presented in Helbing’s models (molecular approach).
      Such integration seems to be the most promising development of this class of tasks due to the fact that the phenomenological approach (Beklaryan-Akopov’s model) enables to introduce natural discretization of a task and then to calculate the increment of all agent’s characteristics at any specific time, and the use of elements of the molecular approach (Helbing’s model) enables to describe the most realistic decision-making system of an agent. This removes a complicated issue of numerical integration of Newton’s equations underlying Helbing’s model and offers explicit calculations of all system characteristics.
      As a result, an agent based model has been devised in AnyLogic simulation modeling system, enabling to investigate agent movement dynamics with due regard to “the crowd effect” in various scenarios, in particular, in extreme situations, when exposure to “crowd crush” and “turbulence” effects exists. 

Citation: Beklaryan A., Akopov A. (2015)

Modelirovanie povedeniya tolpy na osnove intellektual'noy dinamiki vzaimodeystvuyushchikh agentov
[Simulation of human crowd behavior based on intellectual dynamics of interacting agents]. 
Biznes-informatika, no 1 (31), pp. 69-77 (in Russian)

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