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Characterizing Manipulation via Machiavellianism

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  • Jacqueline Sanchez-Rabaza

    (Escuela Superior de Física y Matemáticas, Instituto Politécnico Nacional, School of Physics and Mathematics, National Polytechnic Institute, Edificio 9 U.P. Adolfo Lopez Mateos, Col. San Pedro Zacatenco, Mexico City 07730, Mexico)

  • Jose Maria Rocha-Martinez

    (Escuela Superior de Física y Matemáticas, Instituto Politécnico Nacional, School of Physics and Mathematics, National Polytechnic Institute, Edificio 9 U.P. Adolfo Lopez Mateos, Col. San Pedro Zacatenco, Mexico City 07730, Mexico)

  • Julio B. Clempner

    (Escuela Superior de Física y Matemáticas, Instituto Politécnico Nacional, School of Physics and Mathematics, National Polytechnic Institute, Edificio 9 U.P. Adolfo Lopez Mateos, Col. San Pedro Zacatenco, Mexico City 07730, Mexico)

Abstract

Machiavellianism refers to the propensity of taking advantage of people within a society. Machiavellians have reputations for being cunning and competitive. They are also skilled long-term strategists and planners. Other than their “victories,” there are no other successful conclusions for them. The belief component of Machiavellianism includes cynical views of human nature (e.g., manipulated and manipulating individuals), interpersonal exploitation as a technique (e.g., strategic thinking), and a lack of traditional morality that would forbid their behaviors (e.g., immoral behaviors). This paper focuses on a game that involves manipulation. The game was conceptualized using the best and worst Nash equilibrium points as part of our contribution. We constrained the problem to homogeneous, finite, ergodic, and controllable Bayesian–Markov games. Machiavellian players pretended to be in one state when they were actually in another. Moreover, they pretended to perform one action while actually playing another. All Machiavellian individuals engaged in some form of interpersonal manipulation. Manipulating players exhibited a higher preference compared to manipulated participants. The Pareto frontier is defined as the line where manipulating players play the best Nash equilibrium and manipulated players play the worst Nash equilibrium. It is also considered a sequential Bayesian–Markov manipulation game involving multiple manipulating players and manipulated players. Finally, a tractable characterization of the manipulation equilibrium results is provided. To guarantee that the game’s solution converged into a singular solution, we used Tikhonov’s penalty regularization method. A numerical example describes the results of our model.

Suggested Citation

  • Jacqueline Sanchez-Rabaza & Jose Maria Rocha-Martinez & Julio B. Clempner, 2023. "Characterizing Manipulation via Machiavellianism," Mathematics, MDPI, vol. 11(19), pages 1-19, September.
  • Handle: RePEc:gam:jmathe:v:11:y:2023:i:19:p:4143-:d:1251947
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    References listed on IDEAS

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    1. Luis Rayo & Ilya Segal, 2010. "Optimal Information Disclosure," Journal of Political Economy, University of Chicago Press, vol. 118(5), pages 949-987.
    2. Dirk Bergemann & Stephen Morris, 2016. "Information Design, Bayesian Persuasion, and Bayes Correlated Equilibrium," American Economic Review, American Economic Association, vol. 106(5), pages 586-591, May.
    3. Vijay Krishna & John Morgan, 2001. "A Model of Expertise," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 116(2), pages 747-775.
    4. Faruk Gul & Wolfgang Pesendorfer, 2012. "The War of Information," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 79(2), pages 707-734.
      • Gul, Faruk & Pesendorfer, Wolfgang, 2010. "The War of Information," Papers 9-13-2010, Princeton University, Research Program in Political Economy.
    5. Hao Li & Xianwen Shi, 2017. "Discriminatory Information Disclosure," American Economic Review, American Economic Association, vol. 107(11), pages 3363-3385, November.
    6. Gentzkow, Matthew & Kamenica, Emir, 2017. "Bayesian persuasion with multiple senders and rich signal spaces," Games and Economic Behavior, Elsevier, vol. 104(C), pages 411-429.
    7. Mark Bagnoli & Barton L. Lipman, 1996. "Stock Price Manipulation Through Takeover Bids," RAND Journal of Economics, The RAND Corporation, vol. 27(1), pages 124-147, Spring.
    8. Bergemann, Dirk & Pesendorfer, Martin, 2007. "Information structures in optimal auctions," Journal of Economic Theory, Elsevier, vol. 137(1), pages 580-609, November.
    9. Isabelle Brocas & Juan Carrillo & Thomas Palfrey, 2012. "Information gatekeepers: theory and experimental evidence," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 51(3), pages 649-676, November.
    10. Julio B. Clempner, 2017. "A Game Theory Model for Manipulation Based on Machiavellianism: Moral and Ethical Behavior," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 20(2), pages 1-12.
    11. Péter Eső & Balázs Szentes, 2007. "Optimal Information Disclosure in Auctions and the Handicap Auction," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 74(3), pages 705-731.
    12. Allen, Franklin & Gorton, Gary, 1992. "Stock price manipulation, market microstructure and asymmetric information," European Economic Review, Elsevier, vol. 36(2-3), pages 624-630, April.
    13. Paul Milgrom & John Roberts, 1986. "Relying on the Information of Interested Parties," RAND Journal of Economics, The RAND Corporation, vol. 17(1), pages 18-32, Spring.
    14. Bardhi, Arjada & Guo, Yingni, 2018. "Modes of persuasion toward unanimous consent," Theoretical Economics, Econometric Society, vol. 13(3), September.
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