IDEAS home Printed from https://ideas.repec.org/p/ssa/lemwps/2012-05.html
   My bibliography  Save this paper

A Dynamical Approach to Conflict Analysis

Author

Listed:
  • Sebastian Ille

Abstract

The Conflict Analysis approach by Hipel and Fraser (1984) is well equipped to model repeated games. Players are assumed to posses a sequential reasoning that allows them to ( not necessarily correctly) anticipate the reaction of other players to their strategies. An individual's best response strategy is thus defined based on this projection, adding additional stability conditions to strategic choice and increasing the set of potential equilibria beyond pure Nash equilibria. Yet, the original Conflict Analysis approach lacks the ability to genuinely model dynamic repeated games, in which past play defines the condition for future interactions. This article will illustrate how the original model can be adapted to include endogenous individual preferences that are defined by the strategic choice of players during past play, allowing to model the reciprocal connection between preferential change and best response play in repeated games. A dummy game serves as an exemplar and helps to visualise the results obtained from this extension.

Suggested Citation

  • Sebastian Ille, 2012. "A Dynamical Approach to Conflict Analysis," LEM Papers Series 2012/05, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  • Handle: RePEc:ssa:lemwps:2012/05
    as

    Download full text from publisher

    File URL: http://www.lem.sssup.it/WPLem/files/2012-05.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fagiolo, Giorgio & Dosi, Giovanni, 2003. "Exploitation, exploration and innovation in a model of endogenous growth with locally interacting agents," Structural Change and Economic Dynamics, Elsevier, vol. 14(3), pages 237-273, September.
    2. Jason Potts, 2000. "The New Evolutionary Microeconomics," Books, Edward Elgar Publishing, number 2258.
    3. Giovanni Dosi & Mike Hobday & Luigi Marengo, 2000. "Problem-Solving Behaviours, Organisational Forms and the Complexity of Tasks," LEM Papers Series 2000/06, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    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. Delli Gatti,Domenico & Fagiolo,Giorgio & Gallegati,Mauro & Richiardi,Matteo & Russo,Alberto (ed.), 2018. "Agent-Based Models in Economics," Cambridge Books, Cambridge University Press, number 9781108400046.
    2. Safarzyńska, Karolina & Brouwer, Roy & Hofkes, Marjan, 2013. "Evolutionary modelling of the macro-economic impacts of catastrophic flood events," Ecological Economics, Elsevier, vol. 88(C), pages 108-118.
    3. Thomas Brenner & Claudia Werker, 2006. "A Practical Guide to Inference in Simulation Models," Papers on Economics and Evolution 2006-02, Philipps University Marburg, Department of Geography.
    4. Andrew Mearman, 2010. "What is this thing called ‘heterodox economics’?," Working Papers 1006, Department of Accounting, Economics and Finance, Bristol Business School, University of the West of England, Bristol.
    5. Noel Castree & David J. Keeling & Jerald Podair & Michael Pryke & Duncan W. Scott & Paul Lambe & Robert McMaster & Michael Slivka, 2005. "Book Reviews," Urban Studies, Urban Studies Journal Limited, vol. 42(8), pages 1471-1484, July.
    6. Lamperti, Francesco & Roventini, Andrea & Sani, Amir, 2018. "Agent-based model calibration using machine learning surrogates," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 366-389.
    7. Giorgio Fagiolo & Mattia Guerini & Francesco Lamperti & Alessio Moneta & Andrea Roventini, 2017. "Validation of Agent-Based Models in Economics and Finance," LEM Papers Series 2017/23, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    8. Coronese, Matteo & Occelli, Martina & Lamperti, Francesco & Roventini, Andrea, 2023. "AgriLOVE: Agriculture, land-use and technical change in an evolutionary, agent-based model," Ecological Economics, Elsevier, vol. 208(C).
    9. Jeroen Van den Bergh & Frans Oosterhuis, 2005. "An Evolutionary Economic Analysis of Energy Transitions," ERSA conference papers ersa05p823, European Regional Science Association.
    10. Marek Hudik, 0. "Equilibrium as compatibility of plans," Theory and Decision, Springer, vol. 0, pages 1-20.
    11. Chakravarty, Sugato & Feinberg, Richard & Rhee, Eun-Young, 2004. "Relationships and individuals' bank switching behavior," Journal of Economic Psychology, Elsevier, vol. 25(4), pages 507-527, August.
    12. Sun Hi Yoo & DongKyu Won, 2018. "Simulation of Weak Signals of Nanotechnology Innovation in Complex System," Sustainability, MDPI, vol. 10(2), pages 1-14, February.
    13. Félix-Fernando Muñoz & María-Isabel Encinar, 2019. "Some elements for a definition of an evolutionary efficiency criterion," Journal of Evolutionary Economics, Springer, vol. 29(3), pages 919-937, July.
    14. James Caton & Richard E. Wagner, 2015. "Volatility in Catallactical Systems: Austrian Cycle Theory Revisited," Advances in Austrian Economics, in: New Thinking in Austrian Political Economy, volume 19, pages 95-117, Emerald Group Publishing Limited.
    15. Kurt Dopfer, 2012. "The origins of meso economics," Journal of Evolutionary Economics, Springer, vol. 22(1), pages 133-160, January.
    16. Jason Potts, 2007. "Evolutionary Institutional Economics," Journal of Economic Issues, Taylor & Francis Journals, vol. 41(2), pages 341-350, June.
    17. Giorgio Fagiolo & Daniele Giachini & Andrea Roventini, 2020. "Innovation, finance, and economic growth: an agent-based approach," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(3), pages 703-736, July.
    18. Brendan Markey-Towler, 2018. "A formal psychological theory for evolutionary economics," Journal of Evolutionary Economics, Springer, vol. 28(4), pages 691-725, September.
    19. Foster, John & Metcalfe, J. Stan, 2012. "Economic emergence: An evolutionary economic perspective," Journal of Economic Behavior & Organization, Elsevier, vol. 82(2), pages 420-432.
    20. Jurgen Essletzbichler & David Rigby, 2005. "Technological evolution as creative destruction of process heterogeneity: evidence from US plant-level data," Economic Systems Research, Taylor & Francis Journals, vol. 17(1), pages 25-45.

    More about this item

    Keywords

    Game Theory; Repeated Games; Computational Methods; Non-Nash Equilibria; Dominated Strategies;
    All these keywords.

    JEL classification:

    • C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium
    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools
    • 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
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations

    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:ssa:lemwps:2012/05. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/labssit.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.