Научный журнал Моделирование, оптимизация и информационные технологииThe scientific journal Modeling, Optimization and Information Technology
cетевое издание
issn 2310-6018

AGENT-BASED MODELING OF SOCIAL-POLITICAL SYSTEMS AND PROCESSES: HISTORY OF DEVELOPMENT AND FUTURES FOR PRACTICAL APPLICATION

Ageeva A.F.  

UDC 32.019.5, 323.2, 324, 327, 329, 519.682
DOI: 10.26102/2310-6018/2019.27.4.005

  • Abstract
  • List of references
  • About authors

The article provides an overview of agent-based models that reproduce the structure of sociopolitical systems and dynamics of international processes and socio-political phenomena. The effectiveness and futures of the practical application of agent-based modeling in the field of political knowledge are scientifically proved. An analysis of the conceptual and construction features of agentbased models considered in the scientific review demonstrates the advantages of agent-based modeling for realization applied interdisciplinary projects and research tasks based on the synthesis of several disciplines within the framework of public and political knowledge: political sociology and political psychology, history and archeology, international relations and social culturology. The potentialities and advantages of agent-based modeling in the aspect of its applied meaning for hypothetical testing in the framework of political analysis are shown. A brief history of the practical application of agent-based modeling in the field of political knowledge is presented through a retrospective and structural analysis of models created by prominent political scientists, sociologists and economists, and the impact of their work on the further development of the scientific field is shown. Conclusions regarding the futures for the practical application of simulation in the field of political sciences related with the participation of supercomputer technologies to simulate large-scale socio-political systems, as well as international processes and scenarios that occur on a global scale are presented. The article has been prepared with the support of the Russian Science Foundation (Grant № 19-18- 00240)

1. Makarov V.L., Bakhtizin A.R. Sotsial'noe modelirovanie - novyy komp'yuternyy proryv. Agent-orientirovannye modeli. - M. : Ekonomika, 2013:295.

2. Makarov V.L., Bakhtizin A. R., Sushko E.D. Mul'tiagentnye sistemy i superkomp'yuternye tekhnologii v obshchestvennykh naukakh. Neyrokomp'yutery: razrabotka, primenenie. 2017;5:3-18.

3. Degterev D.A. Rasprostranenie kul'turnykh norm i tsennostey: agentnoe modelirovanie. Vestnik RUDN. 2016;16(1):141-152.

4. Schelling T. Dynamic Models of Segregation. Journal of Mathematical Sociology. 1971; 1(2):143-186.

5. Shelling T. Mikromotivy i makrovybor. - M.: Izdatel'stvo Instituta Gaydara, 2016:344.

6. Anastasopoulos L. An agent-based model simulating political migration and geographic polarization. WP. 2014; Harvard University: 25.

7. Axelrod R. The complexity of cooperation: agent-based models of competition and collaboration. Princeton: Princeton University Press. 1997;:248.

8. Axelrod R. The evolution of cooperation. N.Y.: Basic Books. 2006;:256.

9. Ring J. The diffusion of norms in the international system. PhD thesis. Iowa City: University of Iowa. 2014. [Online]. Available at: http://ir.uiowa.edu/etd/1386

10. Lustick I. Agent-based modeling of collective identity: testing constructivist theory. Journal of Artificial Societies and Social Simulation. 2000;3(1).

11. Lustick, I. Page in JASSS. Available at: http://jasss.soc.surrey.ac.uk/14/1/7/lustick.html

12. Lustick, I. Political Science Department of University of Pennsylvania. International Relationship. Available at: https://www.sas.upenn.edu/polisci/people/standing-faculty/ianlustick

13. Lustick I., Miodownik D. Deliberative democracy and public discourse: the agent-based argument repertoire model. Complexity. 2000;5:13-30.

14. Lustick I. PS-I: a user-friendly agent-based modeling platform for testing theories of political identity and political stability. JASSS. 2002;5(3). Available at: http:// jasss .soc.surrey.ac.uk/5/3/7.html

15. Taylor G., Frederiksen R., Vane R.R., Waltz E. Agent-based simulation of geo-political conflict. Proc. of the 19th Nat. Conf. on Artificial Intelligence, Conf. on Innovative Applications of Artificial Intelligence: San Jose, USA. 2004:884-891.

16. Cederman L.-E. Emergent actors in world politic. Princeton: 1997. Princeton Univ. Press: 290.

17. Cederman L.-E. Endogenizing geopolitical boundaries with agent-based modeling. Proc. of Nat. Acad. Sciences. USA. 2002;99(3):7296-7303.

18. Cederman L.-E. Modeling the size of wars: from billiard balls to sandpiles. American Political Sciences Review. 2003;97(1):135-150.

19. Walbert H.J., Caton J.L., Norgaard J.R. Countries as agents in a global-scale computational model. JASSS. 2018;21(3)4. DOI: 10.18564/jasss.3717

20. Cederman L.-E., Girardin L. Toward realistic computational models of civil wars. Presentation at the Annual Meeting of the American Political Sciences. Association: Chicago. 2007;:25.

21. Epstein J.M. Modeling civil violence: an agent-based computational approach. PNAS. 2002;99(3):7243-7250.

22. Moro A. Why are contemporary political revolutions leaderless? An agent-based explanation. Advances in Practical Applicat. of Agents, Multi-Agent Systems, and Sustainability. 2015:165-174.

23. Bhavnani R., Backer D. Localized ethnic conflict and genocide: accounting for differences in Rwanda and Burundi. Journal of Conflict Resolution. 2000;44(03):283-306.

24. Cioffi-Revilla С., Rouleau M. Mason Rebeland: an agent-based model of politics, environment and Insurgency. International Studies Review. 2010;12(01):31-52.

25. Moro A. Understanding the dynamics of violent political revolutions in an agent-based framework. PLoS ONE. 2016;11(4): e0154175. doi:10.1371/journal.pone.0154175

26. Lustick I.S., Garces M., McCauley T. An agent-based model of counterfactual opportunities for reducing atrocities in Syria, 2011-2014. Series of Occasional Papers. Simon-Skjodt Center for the Prevention of Genocide. 2017;:51.

27. Cioffi-Revilla C. et al. Agent-based modeling simulation of social adaptation and long-term change in Inner Asia. Proc. of The First World Congress in Social Simulation: Tokyo. 2007. DOI: 10.1007/978-4-431-73167-2_18

28. Voinea С.А. On mechanism, process and polity: an agent-based modeling and simulation approach. European Quarterly of Political Attitudes and Mentalities. 2014;3(3):15-45.

29. Geller A., Moss S. Growing QAWM: an evidence-driven declarative model of Afghan power structures. Advances in Complex Systems. 2008;11(2):321-335.

30. Fieldhouse E., Lessard-Phillips L., Edmonds B. Cascade or echo chamber? A complex agent-based simulation of voter turnout. Party Politics. 2016;22(2):241-256.

31. Leifeld P. Polarization of coalitions in an agent-based model of political discourse. Computational Social Networks. 2014;1(7): p. 22.

32. Kim S-Y. A Model of political judgment: an agent-based simulation of candidate evaluation. JASSS. 2011. DOI: 10.18564/jasss.1756

33. Sobkowicz P. Quantitative agent-based model of opinion dynamics: Polish elections of 2015. Plos. 2016. Available at. http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0155098

34. Muis J. Simulating political stability and change in the Netherlands (1998-2002): an agentbased model of party competition with media effects empirically tested. JASSS. 2009. DOI: 10.18564/jasss.1482

35. Ivanov V.G. Agentnoe modelirovanie evolyutsii partiynoy sistemy RF na osnove raspredeleniy Pareto i Khotellinga. Chast' I. Vestnik Rossiyskogo universiteta druzhby narodov. Seriya: Politologiya. 2014;4:58-77.

36. Ivanov V.G. Agentnoe modelirovanie evolyutsii partiynoy sistemy RF na osnove raspredeleniy Pareto i Khotellinga. Chast' II. Vestnik RUDN. Seriya: Politologiya. 2015;1: 5-24.

37. Ageeva A.F. Obzor sovremennykh sistem prinyatiya resheniy, sozdannykh pri pomoshchi agentnogo podkhoda. Elektronnye informatsionnye sistemy. 2018;4(19):29-46.

38. Sushko E.D. Mul'tiagentnaya model' regiona: kontseptsiya, konstruktsiya i realizatsiya. Preprint # WP/2012/292. M.: TsEMI RAN.

39. Klebanov B.I., Moskalev I.M., Begunov N.A., Kritskiy A.V. Mul'tiagentnaya imitatsionnaya model' munitsipal'nogo obrazovaniya. Imitatsionnoe modelirovanie. Teoriya i praktika: sb. dokladov tret'ey Vseros. nauchno-prakticheskoy konf.: SPb. TsNIITS. 2007;2:86-90.

40. Suslov V.I., Novikova T.S., Tsyplakov A.A. Modelirovanie roli gosudarstva v prostranstvennoy agent-orientirovannoy modeli. Ekonomika regiona. 2016;12(3):951-965.

Ageeva Alina Fagimovna
Candidate in Architecture
Email: ageevaalina@yandex.ru

Central Economics and Mathematics Institute of the Russian Academy of Sciences

Moscow, Russian Federation

Keywords: socio-political systems and processes, elections, political analysis, revolutions, international relations, agent-based modeling

For citation: Ageeva A.F. AGENT-BASED MODELING OF SOCIAL-POLITICAL SYSTEMS AND PROCESSES: HISTORY OF DEVELOPMENT AND FUTURES FOR PRACTICAL APPLICATION. Modeling, Optimization and Information Technology. 2019;7(4). Available from: https://moit.vivt.ru/wp-content/uploads/2019/11/Ageeva_4_19_1.pdf DOI: 10.26102/2310-6018/2019.27.4.005 (In Russ).

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