Везде
Application of Agent-based approach to the Modeling of Processes in the Field of Migration Policy
Table of contents
Annotation Estimate Publication content
References Comments
Share
QR
Metrics
Application of Agent-based approach to the Modeling of Processes in the Field of Migration Policy
Annotation
PII
S207751800005912-2-1
DOI
10.18254/S207751800005912-2
Publication type
Article
Статус публикации
Published
Authors
Vladimir Abramov 
ORCID: 0000-0001-5714-2358
Affiliation: Central Economics and Mathematics Institute
Address: Russian Federation, Moscow
Edition
Volume 14 Issue 2
Abstract

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.

Keywords
migration, migration policy, agent based modeling, the EU economy
Received
01.07.2019
Date of publication
08.07.2019
Number of purchasers
92
Views
2162
Readers community rating
0.0 (0 votes)
Cite Download pdf
Additional services access
Additional services for the article
Services benefits
100 RUB / 1.0 SU
Additional services for all issues for 2019
Services benefits
1500 RUB / 15.0 SU

Publication text not found

References

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 http://jasss.soc.surrey.ac.uk/19/1/12.html

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 http://jasss.soc.surrey.ac.uk/21/3/9.html

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 http://jasss.soc.surrey.ac.uk/22/2/2.html

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

Comments

No posts found

Write a review
Translate