[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/unm/umagsb/2017025.html
   My bibliography  Save this paper

Adaptive Learning in Weighted Network Games

Author

Listed:
  • Bayer, Péter

    (Microeconomics & Public Economics, RS: GSBE ETBC)

  • Herings, P. Jean-Jacques

    (Microeconomics & Public Economics, RS: GSBE ETBC)

  • Peeters, Ronald

    (Microeconomics & Public Economics, RS: GSBE ETBC)

  • Thuijsman, Frank

    (DKE Scientific staff, RS: FSE DKE NSO)

Abstract
This paper studies adaptive learning in the class of weighted network games. This class of games includes applications like research and development within interlinked firms, crime within social networks, the economics of pollution, and defense expenditures within allied nations. We show that for every weighted network game, the set of pure Nash equilibria is non-empty and, generically, finite. Pairs of players are shown to have jointly profitable deviations from interior Nash equilibria. If all interaction weights are either non-negative or non-positive, then Nash equilibria are Pareto inefficient. We show that quite general learning processes converge to a Nash equilibrium of a weighted network game if every player updates with some regularity.

Suggested Citation

  • Bayer, Péter & Herings, P. Jean-Jacques & Peeters, Ronald & Thuijsman, Frank, 2017. "Adaptive Learning in Weighted Network Games," Research Memorandum 025, Maastricht University, Graduate School of Business and Economics (GSBE).
    • Handle: RePEc:unm:umagsb:2017025
    DOI: 10.26481/umagsb.2017025
    as

    Download full text from publisher

    File URL: https://cris.maastrichtuniversity.nl/ws/files/16789230/RM17025.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.26481/umagsb.2017025?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Yann Bramoull? & Rachel Kranton & Martin D'Amours, 2014. "Strategic Interaction and Networks," American Economic Review, American Economic Association, vol. 104(3), pages 898-930, March.
    2. Helsley, Robert W. & Zenou, Yves, 2014. "Social networks and interactions in cities," Journal of Economic Theory, Elsevier, vol. 150(C), pages 426-466.
    3. Rosemarie Nagel & Nicolaas J. Vriend, 1999. "An experimental study of adaptive behavior in an oligopolistic market game," Journal of Evolutionary Economics, Springer, vol. 9(1), pages 27-65.
    4. Fudenberg, Drew & Levine, David, 1998. "Learning in games," European Economic Review, Elsevier, vol. 42(3-5), pages 631-639, May.
    5. Allouch, Nizar, 2015. "On the private provision of public goods on networks," Journal of Economic Theory, Elsevier, vol. 157(C), pages 527-552.
    6. Timothy N. Cason & Daniel Friedman, 1997. "Price Formation in Single Call Markets," Econometrica, Econometric Society, vol. 65(2), pages 311-346, March.
    7. Kukushkin, Nikolai S., 2015. "Cournot tatonnement and potentials," Journal of Mathematical Economics, Elsevier, vol. 59(C), pages 117-127.
    8. Lawrence E. Blume & William A. Brock & Steven N. Durlauf & Yannis M. Ioannides, 2010. "Identification of Social Interactions," Discussion Papers Series, Department of Economics, Tufts University 0754, Department of Economics, Tufts University.
    9. Kukushkin, Nikolai S., 2004. "Best response dynamics in finite games with additive aggregation," Games and Economic Behavior, Elsevier, vol. 48(1), pages 94-110, July.
    10. Michael D. König & Xiaodong Liu & Yves Zenou, 2019. "R&D Networks: Theory, Empirics, and Policy Implications," The Review of Economics and Statistics, MIT Press, vol. 101(3), pages 476-491, July.
    11. Renaud Bourlès & Yann Bramoullé & Eduardo Perez‐Richet, 2017. "Altruism in Networks," Econometrica, Econometric Society, vol. 85, pages 675-689, March.
    12. Coralio Ballester & Antoni Calvó-Armengol & Yves Zenou, 2006. "Who's Who in Networks. Wanted: The Key Player," Econometrica, Econometric Society, vol. 74(5), pages 1403-1417, September.
    13. Matthew Elliott & Benjamin Golub, 2019. "A Network Approach to Public Goods," Journal of Political Economy, University of Chicago Press, vol. 127(2), pages 730-776.
    14. Ewerhart, Christian, 2017. "The lottery contest is a best-response potential game," Economics Letters, Elsevier, vol. 155(C), pages 168-171.
    15. John H. Kagel & Dan Levin, 1999. "Common Value Auctions with Insider Information," Econometrica, Econometric Society, vol. 67(5), pages 1219-1238, September.
    16. Belhaj, Mohamed & Bramoullé, Yann & Deroïan, Frédéric, 2014. "Network games under strategic complementarities," Games and Economic Behavior, Elsevier, vol. 88(C), pages 310-319.
    17. Dubey, Pradeep & Haimanko, Ori & Zapechelnyuk, Andriy, 2006. "Strategic complements and substitutes, and potential games," Games and Economic Behavior, Elsevier, vol. 54(1), pages 77-94, January.
    18. Sandler,Todd & Hartley,Keith, 1995. "The Economics of Defense," Cambridge Books, Cambridge University Press, number 9780521447287, September.
    19. Keith Hartley & Todd Sandler (ed.), 2007. "Handbook of Defense Economics," Handbook of Defense Economics, Elsevier, edition 1, volume 2, number 1.
    20. Selten, Reinhard & Stoecker, Rolf, 1986. "End behavior in sequences of finite Prisoner's Dilemma supergames A learning theory approach," Journal of Economic Behavior & Organization, Elsevier, vol. 7(1), pages 47-70, March.
    21. Jackson, Matthew O. & Zenou, Yves, 2015. "Games on Networks," Handbook of Game Theory with Economic Applications,, Elsevier.
    22. Voorneveld, Mark, 2000. "Best-response potential games," Economics Letters, Elsevier, vol. 66(3), pages 289-295, March.
    23. Martin Jensen, 2010. "Aggregative games and best-reply potentials," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 43(1), pages 45-66, April.
    24. Ballester, Coralio & Calvó-Armengol, Antoni, 2010. "Interactions with hidden complementarities," Regional Science and Urban Economics, Elsevier, vol. 40(6), pages 397-406, November.
    25. Bervoets, Sebastian & Faure, Mathieu, 2019. "Stability in games with continua of equilibria," Journal of Economic Theory, Elsevier, vol. 179(C), pages 131-162.
    26. Drew Fudenberg & David K. Levine, 1998. "The Theory of Learning in Games," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262061945, April.
    27. Keith Hartley & Todd Sandler, 2001. "Economics of Alliances: The Lessons for Collective Action," Journal of Economic Literature, American Economic Association, vol. 39(3), pages 869-896, September.
    28. Bramoulle, Yann & Kranton, Rachel, 2007. "Public goods in networks," Journal of Economic Theory, Elsevier, vol. 135(1), pages 478-494, July.
    29. Monderer, Dov & Shapley, Lloyd S., 1996. "Potential Games," Games and Economic Behavior, Elsevier, vol. 14(1), pages 124-143, May.
    30. Leontief, Wassily, 1970. "Environmental Repercussions and the Economic Structure: An Input-Output Approach," The Review of Economics and Statistics, MIT Press, vol. 52(3), pages 262-271, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Bayer, Péter & Herings, P. Jean-Jacques & Peeters, Ronald, 2021. "Farsighted manipulation and exploitation in networks," Journal of Economic Theory, Elsevier, vol. 196(C).
    2. Péter Bayer & György Kozics & Nóra Gabriella Szőke, 2020. "Best-Response Dynamics in Directed Network Games," CEU Working Papers 2020_1, Department of Economics, Central European University.
    3. Orlando, Giuseppe, 2022. "Simulating heterogeneous corporate dynamics via the Rulkov map," Structural Change and Economic Dynamics, Elsevier, vol. 61(C), pages 32-42.
    4. Bayer, Péter & Kozics, György & Szőke, Nóra Gabriella, 2023. "Best-response dynamics in directed network games," Journal of Economic Theory, Elsevier, vol. 213(C).
    5. Meléndez-Jiménez, Miguel A. & Polanski, Arnold, 2020. "Dirty neighbors — Pollution in an interlinked world," Energy Economics, Elsevier, vol. 86(C).
    6. Péter Bayer & György Kozics & Nóra Szőke, 2019. "Best-Response Dynamics in Directed Network Games," CEU Working Papers 2019_3, Department of Economics, Central European University.
    7. P'eter Bayer & Gyorgy Kozics & N'ora Gabriella SzH{o}ke, 2021. "Best-response dynamics in directed network games," Papers 2101.03863, arXiv.org.

    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. Péter Bayer & György Kozics & Nóra Gabriella Szőke, 2020. "Best-Response Dynamics in Directed Network Games," CEU Working Papers 2020_1, Department of Economics, Central European University.
    2. P'eter Bayer & Gyorgy Kozics & N'ora Gabriella SzH{o}ke, 2021. "Best-response dynamics in directed network games," Papers 2101.03863, arXiv.org.
    3. Bayer, Péter & Herings, P. Jean-Jacques & Peeters, Ronald, 2021. "Farsighted manipulation and exploitation in networks," Journal of Economic Theory, Elsevier, vol. 196(C).
    4. Bayer, Péter & Kozics, György & Szőke, Nóra Gabriella, 2023. "Best-response dynamics in directed network games," Journal of Economic Theory, Elsevier, vol. 213(C).
    5. Parise, Francesca & Ozdaglar, Asuman, 2019. "A variational inequality framework for network games: Existence, uniqueness, convergence and sensitivity analysis," Games and Economic Behavior, Elsevier, vol. 114(C), pages 47-82.
    6. Abheek Ghosh & Paul W. Goldberg, 2023. "Best-Response Dynamics in Lottery Contests," Papers 2305.10881, arXiv.org.
    7. Topa, Giorgio & Zenou, Yves, 2015. "Neighborhood and Network Effects," Handbook of Regional and Urban Economics, in: Gilles Duranton & J. V. Henderson & William C. Strange (ed.), Handbook of Regional and Urban Economics, edition 1, volume 5, chapter 0, pages 561-624, Elsevier.
    8. Péter Bayer & György Kozics & Nóra Szőke, 2019. "Best-Response Dynamics in Directed Network Games," CEU Working Papers 2019_3, Department of Economics, Central European University.
    9. Emerson Melo, 2018. "A Variational Approach to Network Games," Working Papers 2018.05, Fondazione Eni Enrico Mattei.
    10. Jackson, Matthew O. & Zenou, Yves, 2015. "Games on Networks," Handbook of Game Theory with Economic Applications,, Elsevier.
    11. Ushchev, Philip & Zenou, Yves, 2020. "Social norms in networks," Journal of Economic Theory, Elsevier, vol. 185(C).
    12. Hiller, Timo, 2022. "A simple model of network formation with competition effects," Journal of Mathematical Economics, Elsevier, vol. 99(C).
    13. Edith Elkind & Abheek Ghosh & Paul W. Goldberg, 2024. "Continuous-Time Best-Response and Related Dynamics in Tullock Contests with Convex Costs," Papers 2402.08541, arXiv.org, revised Oct 2024.
    14. Dike Chukwudi Henry, 2021. "Network Games, Peer Effect and Neutral Transfers," Studies in Economics 2107, School of Economics, University of Kent.
    15. Bochet, Olivier & Faure, Mathieu & Long, Yan & Zenou, Yves, 2020. "Perceived Competition in Networks," CEPR Discussion Papers 15582, C.E.P.R. Discussion Papers.
    16. Allouch, Nizar, 2017. "The cost of segregation in (social) networks," Games and Economic Behavior, Elsevier, vol. 106(C), pages 329-342.
    17. Chen, Ying-Ju & Zenou, Yves & Zhou, Junjie, 2022. "The impact of network topology and market structure on pricing," Journal of Economic Theory, Elsevier, vol. 204(C).
    18. Lionel Richefort, 2018. "Warm-glow giving in networks with multiple public goods," International Journal of Game Theory, Springer;Game Theory Society, vol. 47(4), pages 1211-1238, November.
    19. Belhaj, Mohamed & Bramoullé, Yann & Deroïan, Frédéric, 2014. "Network games under strategic complementarities," Games and Economic Behavior, Elsevier, vol. 88(C), pages 310-319.
    20. Uno, Hiroshi, 2011. "Strategic complementarities and nested potential games," Journal of Mathematical Economics, Elsevier, vol. 47(6), pages 728-732.

    More about this item

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • D74 - Microeconomics - - Analysis of Collective Decision-Making - - - Conflict; Conflict Resolution; Alliances; Revolutions
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • H41 - Public Economics - - Publicly Provided Goods - - - Public Goods

    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:unm:umagsb:2017025. 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: Andrea Willems or Leonne Portz (email available below). General contact details of provider: https://edirc.repec.org/data/meteonl.html .

    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.