IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2211.12475.html
   My bibliography  Save this paper

The impact of moving expenses on social segregation: a simulation with RL and ABM

Author

Listed:
  • Xinyu Li

Abstract

Over the past decades, breakthroughs such as Reinforcement Learning (RL) and Agent-based modeling (ABM) have made simulations of economic models feasible. Recently, there has been increasing interest in applying ABM to study the impact of residential preferences on neighborhood segregation in the Schelling Segregation Model. In this paper, RL is combined with ABM to simulate a modified Schelling Segregation model, which incorporates moving expenses as an input parameter. In particular, deep Q network (DQN) is adopted as RL agents' learning algorithm to simulate the behaviors of households and their preferences. This paper studies the impact of moving expenses on the overall segregation pattern and its role in social integration. A more comprehensive simulation of the segregation model is built for policymakers to forecast the potential consequences of their policies.

Suggested Citation

  • Xinyu Li, 2022. "The impact of moving expenses on social segregation: a simulation with RL and ABM," Papers 2211.12475, arXiv.org.
    • Handle: RePEc:arx:papers:2211.12475
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2211.12475
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wieland, Volker & Wolters, Maik, 2013. "Forecasting and Policy Making," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 239-325, Elsevier.
    2. W. Clark, 1991. "Residential preferences and neighborhood racial segregation: A test of the schelling segregation model," Demography, Springer;Population Association of America (PAA), vol. 28(1), pages 1-19, February.
    3. Farmer, J. Doyne & Axtell, Robert L., 2022. "Agent-Based Modeling in Economics and Finance: Past, Present, and Future," INET Oxford Working Papers 2022-10, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
    4. Joshua M. Epstein & Robert L. Axtell, 1996. "Growing Artificial Societies: Social Science from the Bottom Up," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262550253, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Itzhak Omer, 2005. "How Ethnicity Influences Residential Distributions: An Agent-Based Simulation," Environment and Planning B, , vol. 32(5), pages 657-672, October.
    2. Florence Goffette-Nagot & Pablo Jensen & Sebastian Grauwin, 2009. "Dynamic models of residential segregation: Brief review, analytical resolution and study of the introduction of coordination," Post-Print halshs-00404400, HAL.
    3. Luca Grilli & Domenico Santoro, 2022. "Forecasting financial time series with Boltzmann entropy through neural networks," Computational Management Science, Springer, vol. 19(4), pages 665-681, October.
    4. Henry Wasserman & Gary Yohe, 2001. "Segregation and the Provision of Spatially Defined Local Public Goods," The American Economist, Sage Publications, vol. 45(2), pages 13-24, October.
    5. Alexander J. Laurie & Narendra K. Jaggi, 2003. "Role of 'Vision' in Neighbourhood Racial Segregation: A Variant of the Schelling Segregation Model," Urban Studies, Urban Studies Journal Limited, vol. 40(13), pages 2687-2704, December.
    6. Radi, Davide & Gardini, Laura & Avrutin, Viktor, 2014. "The role of constraints in a segregation model: The symmetric case," Chaos, Solitons & Fractals, Elsevier, vol. 66(C), pages 103-119.
    7. Antoni Rubi-Barcelo, 2013. "Categorical Segregation from a Game Theoretical Approach," Annals of Economics and Finance, Society for AEF, vol. 14(1), pages 85-120, May.
    8. Junfu Zhang, 2011. "Tipping And Residential Segregation: A Unified Schelling Model," Journal of Regional Science, Wiley Blackwell, vol. 51(1), pages 167-193, February.
    9. David O'Sullivan, 2009. "Changing Neighborhoods—Neighborhoods Changing," Sociological Methods & Research, , vol. 37(4), pages 498-530, May.
    10. Marco Catola & Silvia Leoni, 2023. "Pollution Abatement and Lobbying in a Cournot Game. An Agent-Based Modelling approach," Discussion Papers 2023/294, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy.
    11. Mark Fossett & Warren Waren, 2005. "Overlooked Implications of Ethnic Preferences for Residential Segregation in Agent-based Models," Urban Studies, Urban Studies Journal Limited, vol. 42(11), pages 1893-1917, October.
    12. Laura Gardini & Davide Radi, 2018. "A piecewise smooth model of evolutionary game for residential mobility and segregation," Working Papers 1802, University of Urbino Carlo Bo, Department of Economics, Society & Politics - Scientific Committee - L. Stefanini & G. Travaglini, revised 2018.
    13. Luís de Sousa & Alberto Rodrigues da Silva, 2015. "Showcasing a Domain Specific Language for Spatial Simulation Scenarios with case studies," ERSA conference papers ersa15p1044, European Regional Science Association.
    14. Eugenio Caverzasi & Antoine Godin, 2013. "Stock-flow Consistent Modeling through the Ages," Economics Working Paper Archive wp_745, Levy Economics Institute.
    15. Luca Riccetti & Alberto Russo & Mauro Gallegati, 2015. "An agent based decentralized matching macroeconomic model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 10(2), pages 305-332, October.
    16. Michael J. Radzicki, 2003. "Mr. Hamilton, Mr. Forrester, and a Foundation for Evolutionary Economics," Journal of Economic Issues, Taylor & Francis Journals, vol. 37(1), pages 133-173, March.
    17. Gandica, Yerali & Gargiulo, Floriana & Carletti, Timoteo, 2016. "Can topology reshape segregation patterns?," Chaos, Solitons & Fractals, Elsevier, vol. 90(C), pages 46-54.
    18. Kazuya Yamamoto, 2015. "Mobilization, Flexibility of Identity, and Ethnic Cleavage," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(2), pages 1-8.
    19. Barbara Rossi, 2013. "Exchange Rate Predictability," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1063-1119, December.
    20. Dirk Helbing & Thomas U. Grund, 2013. "Editorial: Agent-Based Modeling And Techno-Social Systems," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 16(04n05), pages 1-3.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2211.12475. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.