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Clever Agents in Young's Evolutionary Bargaining Model

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Author Info

  • Weibull, Jörgen W.

    ()
    (The Research Institute of Industrial Economics)

  • Saez-Marti, Maria

    ()
    (Stockholm School of Economics)

Abstract

In the models of Young (1993a,b), boundedly rational individuals are recurrently matched to play a game, and they play myopic best replies to the recent history of play. It could therefore be an advantage to instead play a myopic best reply to the myopic best reply, something boundedly rational players might conceivably also do. We investigate this possibility in the context of Young's (1993b)bargaining model. It turns out that "cleverness" in this respect indeed does have an advantage in some cases. However, if all individuals are equally informed about past play, in a statistical sense, then the Nash bargaining solution remains the unique long-run outcome when the mutation rate goes to zero.

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Bibliographic Info

Paper provided by Research Institute of Industrial Economics in its series Working Paper Series with number 507.

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Length: 11 pages
Date of creation: 09 Nov 1998
Date of revision:
Publication status: Published in Journal of Economic Theory, 1999, pages 268-279.
Handle: RePEc:hhs:iuiwop:0507

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Postal: Research Institute of Industrial Economics, Box 55665, SE-102 15 Stockholm, Sweden
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Keywords: Evolution; Bargaining; Bounded rationality; Game theory;

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Cited by:
  1. Matros, Alexander, 2012. "Altruistic versus egoistic behavior in a Public Good game," Journal of Economic Dynamics and Control, Elsevier, vol. 36(4), pages 642-656.
  2. Matros, Alexander, 2000. "Clever agents in adaptive learning," Working Paper Series in Economics and Finance 403, Stockholm School of Economics.
  3. Kevin Hasker, 2014. "The Emergent Seed: A Representation Theorem for Models of Stochastic Evolution and two formulas for Waiting Time," Levine's Working Paper Archive 786969000000000954, David K. Levine.
  4. Herbert Dawid & Joern Dermietzel, 2006. "How Robust is the Equal Split Norm? Responsive Strategies, Selection Mechanisms and the Need for Economic Interpretation of Simulation Parameters," Computational Economics, Society for Computational Economics, vol. 28(4), pages 371-397, November.
  5. Josephson, Jens, 2009. "Stochastic adaptation in finite games played by heterogeneous populations," Journal of Economic Dynamics and Control, Elsevier, vol. 33(8), pages 1543-1554, August.
  6. Sandholm,W.H., 1999. "Almost global convergence to p-dominant equilibrium," Working papers 37, Wisconsin Madison - Social Systems.
  7. Ellingsen, Tore & Robles, Jack, 2000. "Does Evolution Solve the Hold-up Problem?," Working Paper Series in Economics and Finance 358, Stockholm School of Economics.
  8. Rozen, Kareen, 2013. "Conflict leads to cooperation in demand bargaining," Journal of Economic Behavior & Organization, Elsevier, vol. 87(C), pages 35-42.
  9. Alexander Matros, 2006. "Altruistic Versus Rational Behavior in a Public Good Game," Working Papers 309, University of Pittsburgh, Department of Economics, revised Sep 2008.
  10. Blume, Andreas & Dieckmann, Tone, 1998. "Learning to Communicate in Cheap-Talk Games," Working Papers 98-12, University of Iowa, Department of Economics.
  11. Francesco Squintani, 1999. "Moral Hazard," Discussion Papers 1269, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
  12. Kevin Hasker, 2004. "The Emergent Seed : Simplifying the Analysis of Dynamic Evolution," Departmental Working Papers 0406, Bilkent University, Department of Economics.

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