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Intergroup Prisoner’s Dilemma with Intragroup Power Dynamics

Author

Listed:
  • Ion Juvina

    (Department of Psychology, Carnegie Mellon University, Pittsburgh, PA 15213, USA)

  • Christian Lebiere

    (Department of Psychology, Carnegie Mellon University, Pittsburgh, PA 15213, USA)

  • Jolie M. Martin

    (Dynamic Decision Making Laboratory, Social and Decision Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA)

  • Cleotilde Gonzalez

    (Dynamic Decision Making Laboratory, Social and Decision Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA)

Abstract

The Intergroup Prisoner’s Dilemma with Intragroup Power Dynamics (IPD^2) is a new game paradigm for studying human behavior in conflict situations. IPD^2 adds the concept of intragroup power to an intergroup version of the standard Repeated Prisoner’s Dilemma game. We conducted a laboratory study in which individual human participants played the game against computer strategies of various complexities. The results show that participants tend to cooperate more when they have greater power status within their groups. IPD^2 yields increasing levels of mutual cooperation and decreasing levels of mutual defection, in contrast to a variant of Intergroup Prisoner’s Dilemma without intragroup power dynamics where mutual cooperation and mutual defection are equally likely. We developed a cognitive model of human decision making in this game inspired by the Instance-Based Learning Theory (IBLT) and implemented within the ACT-R cognitive architecture. This model was run in place of a human participant using the same paradigm as the human study. The results from the model show a pattern of behavior similar to that of human data. We conclude with a discussion of the ways in which the IPD^2 paradigm can be applied to studying human behavior in conflict situations. In particular, we present the current study as a possible contribution to corroborating the conjecture that democracy reduces the risk of wars.

Suggested Citation

  • Ion Juvina & Christian Lebiere & Jolie M. Martin & Cleotilde Gonzalez, 2011. "Intergroup Prisoner’s Dilemma with Intragroup Power Dynamics," Games, MDPI, vol. 2(1), pages 1-31, February.
  • Handle: RePEc:gam:jgames:v:2:y:2011:i:1:p:21-51:d:11252
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    References listed on IDEAS

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    1. Ido Erev & Eyal Ert & Alvin E. Roth, 2010. "Erev, I. et al . A Choice Prediction Competition for Market Entry Games: An Introduction. Games 2010, 1 , 117-136," Games, MDPI, vol. 1(3), pages 1-5, July.
    2. Tyran, Jean-Robert, 2003. "Behavioral Game Theory. Experiments in Strategic Interaction: Colin F. Camerer, Princeton University Press, Princeton, New Jersey, 2003, p. 550, Price $65.00/[UK pound]42.95, ISBN 0-691-09039-4," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 32(6), pages 717-720, December.
    3. Putnam, Robert D., 1988. "Diplomacy and domestic politics: the logic of two-level games," International Organization, Cambridge University Press, vol. 42(3), pages 427-460, July.
    4. Gary Bornstein, 2002. "Intergroup conflict: Individual, group and collective interests," Discussion Paper Series dp297, The Federmann Center for the Study of Rationality, the Hebrew University, Jerusalem.
    5. Erev, Ido & Roth, Alvin E, 1998. "Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria," American Economic Review, American Economic Association, vol. 88(4), pages 848-881, September.
    6. Ido Erev & Eyal Ert & Alvin E. Roth, 2010. "A Choice Prediction Competition for Market Entry Games: An Introduction," Games, MDPI, vol. 1(2), pages 1-20, May.
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