Abstract
There are three main simulation paradigms. They are as follows: discrete-event modeling, system dynamics and agent-based modeling. In this set, the agent-based paradigm is the one geared towards economic and social system modelling, and, thus, called ‘the right mathematics for the social sciences’. When it was decided to explore communications in an economic system, it has become evident that the most suitable technology for economic system model engineering is the agent-based technology, whose concepts and software toolkits have been developed greatly during several past decades. This paper discusses the process of toolkit choice for communication model engineering, reveals some problems that can be solved with this model and delivers some specific results which were obtained via simulations. Some interesting phenomena were revealed while experimenting with this model.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
C.M. Macal, M.J. North, Agent-based modeling and simulation, in Proceedings of the 2009 Winter Simulation Conference, pp. 86–98(2009)
C.M. Macal, M.J. North, Tutorial on agent-based modelling and simulation. J. Simul. 4, 151–162 (2010)
S.-H. Chen, Varieties of agent-based computational economics: a historical and interdisciplinary perspective. J. Econ. Dyn. Control (2011)
E. Bonabeau, Agent-based modeling: methods and techniques for simulating human systems. PNAS 99(suppl. 3), 7280–7287 (2002)
A. Troisi, V. Wong, M.A. Ratner, An agent-based approach for modeling molecular self-organization. Proc. Natl. Acad. Sci. USA 102(2), 255–260 (2005). www.pnas.org/cgi/doi/10.1073/pnas.0408308102. Accessed 12 Jan 2018
E. Tatara, I. Birol, F. Teymour, A. Cinar, Agent-based control of autocatalytic replicators in networks of reactors. J. Comput. Chem. Eng. 29, 807–815 (2005)
K.J. Mock, J.W. Testa, An Agent-Based Model of Predator-Prey Relationships Between Transient Killer Whales and Other Marine Mammals (University of Alaska Anchorage, Anchorage, AK). www.math.uaa.alaska.edu/orca/. Accessed 11 Jan 2018
V.A. Folcik, G.C. An, C.G. Orosz, The basic immune simulator: an agent-based model to study the interactions between innate and adaptive immunity. Theor. Bio. Med. Model. 4(1), 39–56 (2007)
M. Gavin, Agent-based modeling and historical simulation. Digit. Hum. Q. 8(1) (2014)
N. Luhmann, Social Systems. Sketch of the General Theory (Science, St. Petersburg, 2007), 668 p
P.L. Borrill, L. Tesfatsion, Agent-based modeling: the right mathematics for the social sciences, in Working Paper No 10023, July (2010)
L. Tesfatsion, Agent-based computational economics. www.econ.iastate.edu/tesfatsi/ace.htm. Accessed 19 Jan 2018
V.B. Kashkin, Intoduction To Communication Theory: A Tutorial (Flinta, Moscow, 2013), 224 p
D.B. Berg, O.M. Zvereva, S. Akenov, «Economic Microscope»: the agent-based model set as an instrument in an economic system research, in ICNAAM 2016 Conference Proceeding, Vol. 1863, Paper No 050006, 21 July 2017
V.V. Leontief, Essays in economics. Theories, theorizing, facts and policies (Politizdat, Moscow, 1990), 415 p
C. Nikolai, G. Madey, Tools of the trade: a survey of various agent based modeling platforms. J. Artif. Soc. Soc. Simul. 12(2) (2009)
S.L. Railsback, S.F. Lytinen, S. Jackson, Agent-based simulation platforms: review and development recommendations. Simulation 82, 609–623 (2006)
S.L. Lytinen, S.F. Railsback, The evolution of agent-based simulation platforms: a review of NetLogo 5.0 and ReLogo, in Proceedings of the Fourth International Symposium on Agent-Based Modeling and Simulation (2011). http://www2.econ.iastate.edu/tesfatsi/NetLogoReLogoReview.LytinenRailsback2012.pdf. Accessed 21 Jan 2018
U. Wilensky, NetLogo (Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL, 1999). http://ccl.northwestern.edu/netlogo/. Accessed 20 Jan 2018
B.A. Lietar, The Future of Money. Creating New Wealth, Work and Wiser World (KRPA Olymp: AST: Astrel, Moscow, 2007), 493 p
Acknowledgements
The work was supported by Act 211 Government of the Russian Federation, contract N 02.A03.21.0006.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Zvereva, O.M. (2020). Investigation of Money Turnover in the Computer Agent-Based Model. In: Kumkov, S., Shabunin, S., Syngellakis, S. (eds) Advances in Information Technologies, Telecommunication, and Radioelectronics. Innovation and Discovery in Russian Science and Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-37514-0_9
Download citation
DOI: https://doi.org/10.1007/978-3-030-37514-0_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-37513-3
Online ISBN: 978-3-030-37514-0
eBook Packages: EngineeringEngineering (R0)