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Learning by (limited) forward looking players

  • Mengel Friederike

    (METEOR)

We present a model of adaptive economic agents that are k periods forward looking. Agents in our model are randomly matched to interact in finitely repeated games. They form beliefs by relying on their past experience in the same situation (after the same recent history) and then best respond to these beliefs looking k periods ahead. We establish almost sure convergence of our stochastic process and characterize absorbing sets. These can be very different from the predictions in both the fully rational model and the adaptive, but myopic case. In particular we find that also Non-Nash outcomes can be sustained almost all the time whenever they are individually rational and satisfy an efficiency condition. We then characterize stochastically stable states in 2×2 games and show that under certain conditions the efficient action in Prisoner''s Dilemma games and Coordination games can be singled out as uniquely stochastically stable. We show that our results are consistent with typical patterns observed in experiments on finitely repeated Prisoner''s Dilemma games. Finally, if populations are composed of some myopic and some forward looking agents parameter constellations exists such that either might obtain higher average payoffs.

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File URL: http://digitalarchive.maastrichtuniversity.nl/fedora/objects/guid:7a45f377-c44b-4c60-900d-31d6af1aa5a8/datastreams/ASSET1/content
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Paper provided by Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR) in its series Research Memorandum with number 053.

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Date of creation: 2008
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Handle: RePEc:unm:umamet:2008053
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  1. Andreoni, James A & Miller, John H, 1993. "Rational Cooperation in the Finitely Repeated Prisoner's Dilemma: Experimental Evidence," Economic Journal, Royal Economic Society, vol. 103(418), pages 570-85, May.
  2. Kyle Hyndman & Erkut Y. Ozbay & Andrew Schotter & Wolf Ze’ev Ehrblatt, 2012. "Convergence: An Experimental Study Of Teaching And Learning In Repeated Games," Journal of the European Economic Association, European Economic Association, vol. 10(3), pages 573-604, 05.
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  7. Jeheil Phillippe, 1995. "Limited Horizon Forecast in Repeated Alternate Games," Journal of Economic Theory, Elsevier, vol. 67(2), pages 497-519, December.
  8. Jehiel, Philippe, 1998. "Learning to Play Limited Forecast Equilibria," Games and Economic Behavior, Elsevier, vol. 22(2), pages 274-298, February.
  9. Jehiel, Philippe, 2001. "Limited Foresight May Force Cooperation," Review of Economic Studies, Wiley Blackwell, vol. 68(2), pages 369-91, April.
  10. Antoine Terracol & Jonathan Vaksmann, 2009. "Dumbing down rational players: Learning and teaching in an experimental game," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00607223, HAL.
  11. Young, H Peyton, 1993. "The Evolution of Conventions," Econometrica, Econometric Society, vol. 61(1), pages 57-84, January.
  12. Stahl II, D.O., 1991. "Evolution of Smart Players," Papers 9166, Tilburg - Center for Economic Research.
  13. Basu, K. & Weibull, J.W., 1990. "Strategy Subsets Closed Under Rational Behaviour," Papers 479, Stockholm - International Economic Studies.
  14. Drew Fudenberg & David K. Levine, 1996. "The Theory of Learning in Games," Levine's Working Paper Archive 624, David K. Levine.
  15. Myerson, Roger B. & Pollock, Gregory B. & Swinkels, Jeroen M., 1991. "Viscous population equilibria," Games and Economic Behavior, Elsevier, vol. 3(1), pages 101-109, February.
  16. Camerer, Colin F. & Ho, Teck-Hua & Chong, Juin-Kuan, 2002. "Sophisticated Experience-Weighted Attraction Learning and Strategic Teaching in Repeated Games," Journal of Economic Theory, Elsevier, vol. 104(1), pages 137-188, May.
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