Application of Agent-based approach to the Modeling of Processes in the Field of Migration Policy
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Application of Agent-based approach to the Modeling of Processes in the Field of Migration Policy
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Vladimir Abramov 
Affiliation: Central Economics and Mathematics Institute
Address: Russian Federation, Moscow

The article is devoted to the analysis of existing experience in the application of agent based approach by modeling migration processes carried out for ongoing development of complex agent based models to simulate processes in the field of migration policy. Analysis showed that despite the advantages demonstrated by the agent-based approach compared with traditional methods of demographic research simulation reveals various difficulties in terms of simulating migration processes that nevertheless do not underestimate advantages of agent and other existing modeling approaches. Hybrid population-based agent modeling is a new emerging field of study that showed advantages by implementing this approach.

migration, migration policy, agent based modeling, the EU economy
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1. Bakhtizin A.R. Agent-orientirovannye modeli ehkonomiki. // M.: Ehkonomika, 2008.

2. Makarov V.L., Bakhtizin A.R., Sushko E.D., Abramov V.I. Komp'yuternoe modelirovanie v upravlenii ehkonomikoj (metodologicheskaya osnova dlya strategicheskogo planirovaniya) // Gosudarstvennyj audit. Pravo. Ehkonomika, № 3, 2017.

3. Burch T. K. Model-Based Demography. // Essays on Integrating Data, Technique and Theory, 2018, DOI:10.1007/978-3-319-65433-1.

4. Constant A., Massey D. S. Return Migration by German Guestworkers: Neoclassical versus New Economic Theories. // International Migration, 2002, 40(4), p. 5–38.

5. Courgeau D., Bijak J., Franck R., Silverman E. Model-based demography: Towards a research agenda. // Agent-Based Modelling in Population Studies: Concepts, Methods, and Applications, 2016, p. 29–51.

6. Ewald R., Uhrmacher A. M. SESSL: A domain-specific language for simulation experiments. // ACM Transactions on Modeling and Computer Simulation, 2014, 24(2).

7. Harris J. R., Todaro M. P. Migration, Unemployment and Development: a Two-Sector Analysis. // American Economic Review, 1970, 60(1), p. 126–142.

8. Hobcraft J. Towards a scientific understanding of demographic behaviour. // Population – English Edition, 2007, 62(1), p. 47–51.

9. Klabunde A., Zinn S., Willekens F., Leuchter M. Multistate modelling extended by behavioural rules: An application to migration. // Population Studies, 2017, 71, p. 51–67.

10. Moeckel R., Spiekermann K., Wegener M. Creating a synthetic population. // Proceedings of the 8th International Conference on Computers in Urban Planning and Urban Management (CUPUM), 2003.

11. Morand E., Toulemon L., Pennec S., Baggio R., Billari F. Demographic modelling: The state of the art. // SustainCity working paper, 2010.

12. Pei-jun Y., Xiao W., Cheng Chenc Y., Fei-yue W. Hybrid Agent Modeling in Population Simulation: Current Approaches and Future Directions // Journal of Artificial Societies and Social Simulation, 2016, 19(1)12

13. Portes A. Social Capital: Its Origins and Applications in Modern Sociology. // Annual Review of Sociology, 1998, 24(1), 1–24, DOI:10.1146/annurev.soc.24.1.1.

14. Reinhardt O., Hilton J., Warnke T., Bijak J., Uhrmacher A. Streamlining Simulation Experiments with Agent-Based Models in Demography // Journal of Artificial Societies and Social Simulation, 2018, 21(3)9

15. Silverman E., Bijak J., Hilton J., Cao V. D., Noble J. When demography met social simulation: A tale of two modeling approaches. // Journal of Artificial Societies and Social Simulation 2013, 16(4), 9.

16. Simon M. Path Dependency and Adaptation: The Effects of Policy on Migration Systems // Journal of Artificial Societies and Social Simulation 2019, 22(2)2

17. Warnke T., Steiniger A., Uhrmacher A. M., Klabunde A., Willekens F. ML3: A Language for Compact Modeling of Linked Lives in Computational Demography. // Proceedings of the 2015 Winter Simulation Conference, 2015, p. 2764–2775, DOI:10.1109/WSC.2015.7408382

18. Watts D. J., Strogatz S. H. Collective dynamics of small-world networks. // Nature, 1998, 393(6684), p. 440–442, DOI:10.1038/30918


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