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Learning in Networks: a survey

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  • Goyal, Sanjeev

Abstract

This paper presents a survey of research on learning with a special focus on the structure of interaction between individual entities. The structure is formally modelled as a network: the nodes of the network are individuals while the arcs admit a variety of interpretations (ranging from information channels to social and economic ties). I first examine the nature of learning about optimal actions for a given network architecture. I then discuss learning about optimal links and actions in evolving networks.

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  • Goyal, Sanjeev, 2003. "Learning in Networks: a survey," Economics Discussion Papers 9983, University of Essex, Department of Economics.
    • Handle: RePEc:esx:essedp:9983
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    Cited by:

    1. Sanjeev Goyal & Marco J. van der Leij & José Luis Moraga-Gonzalez, 2006. "Economics: An Emerging Small World," Journal of Political Economy, University of Chicago Press, vol. 114(2), pages 403-432, April.
    2. Alessio D'Ignazio & Emanuele Giovannetti, 2006. "From Exogenous To Endogenous Economic Networks: Internet Applications," Journal of Economic Surveys, Wiley Blackwell, vol. 20(5), pages 757-796, December.
    3. Kahanec, Martin, 2006. "Ethnic Specialization and Earnings Inequality: Why Being a Minority Hurts but Being a Big Minority Hurts More," IZA Discussion Papers 2050, Institute of Labor Economics (IZA).
    4. Alexander Eim & Dirk Lamprecht & Mark Wipprich, 2006. "Die Netzwerke der Sparkassen-Finanzgruppe und des genossenschaftlichen FinanzVerbundes: Zukunftsperspektiven des Dreisäulensystems," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 75(4), pages 53-72.
    5. Kahanec, M., 2006. "Social interaction in the labor market : Essays on earnings inequality, labor substitutability, and segregation," Other publications TiSEM 9591d415-dea7-4f42-89e8-0, Tilburg University, School of Economics and Management.
    6. Schuster, Stephan, 2010. "Network Formation with Adaptive Agents," MPRA Paper 27388, University Library of Munich, Germany.
    7. Jaromír Kovářík & Friederike Mengel & José Gabriel Romero, 2018. "Learning in network games," Quantitative Economics, Econometric Society, vol. 9(1), pages 85-139, March.
      • Kovarik, Jaromir & Mengel, Friederike & Romero, José Gabriel, 2012. "Learning in Network Games," IKERLANAK http://www-fae1-eao1-ehu-, Universidad del País Vasco - Departamento de Fundamentos del Análisis Económico I.
    8. D'Ignazio, A. & Giovannetti, E., 2004. "From Exogenous to Endogenous Networks: Internet Applications," Cambridge Working Papers in Economics 0445, Faculty of Economics, University of Cambridge.
    9. Kariv, Shachar, 2004. "A Theory and Experiments of Learning in Social Networks," Santa Cruz Department of Economics, Working Paper Series qt8853k4jd, Department of Economics, UC Santa Cruz.
    10. Schuster, Stephan, 2012. "Applications in Agent-Based Computational Economics," MPRA Paper 47201, University Library of Munich, Germany.

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