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Simultaneous evolution of learning rules and strategies

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  • Kirchkamp, Oliver

Abstract

We study a model of local evolution. Agents are located on a network and interact strategically with their neighbours. Strategies are chosen with the help of learning rules that are based on the success of strategies observed in the neighbourhood. The standard literature on local evolution assumes learning rules to be exogenous and fixed. In this paper we consider a specific evolutionary dynamics that determines learning rules endogenously. We find with the help of simulations that in the long run learning rules behave rather deterministically but are asymmetric in the sense that while learning they put more weight on the learning players' experience than on the observed players' one. Nevertheless stage game behaviour under these learning rules is similar to behaviour with symmetric learning rules.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Economic Behavior & Organization.

Volume (Year): 40 (1999)
Issue (Month): 3 (November)
Pages: 295-312

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Handle: RePEc:eee:jeborg:v:40:y:1999:i:3:p:295-312

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  1. Binmore, K. & Samuelson, L., 1994. "Muddling Through: Noisy Equilibrium selection," Working papers 9410, Wisconsin Madison - Social Systems.
  2. Schlag,Karl, . "Dynamic stability in the repeated prisoners dilemma," Discussion Paper Serie B 243, University of Bonn, Germany.
  3. Glen Ellison, 2010. "Learning, Local Interaction, and Coordination," Levine's Working Paper Archive 391, David K. Levine.
  4. Kirchkamp, Oliver, 1995. "Spatial Evolution of Automata in the Prisoners' Dilemma," Discussion Paper Serie B 330, University of Bonn, Germany.
  5. Schlag, Karl H., 1994. "Why Imitate, and if so, How? Exploring a Model of Social Evolution," Discussion Paper Serie B 296, University of Bonn, Germany.
  6. Eshel, I. & Samuelson, L. & Shaked, A., 1996. "Altruists, Egoists and Hooligans in a Local Interaction Model," Working papers 9612, Wisconsin Madison - Social Systems.
  7. Eshel, Ilan & Samuelson, Larry & Shaked, Avner, 1998. "Altruists, Egoists, and Hooligans in a Local Interaction Model," American Economic Review, American Economic Association, vol. 88(1), pages 157-79, March.
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Cited by:
  1. Kirchkamp, Oliver & Nagel, Rosemarie, 2003. "No imitation - on local and group interaction, learning and reciprocity in prisoners\," Sonderforschungsbereich 504 Publications 03-04, Sonderforschungsbereich 504, Universität Mannheim & Sonderforschungsbereich 504, University of Mannheim.
  2. Ludo Waltman & Nees Eck & Rommert Dekker & Uzay Kaymak, 2013. "An Evolutionary Model of Price Competition Among Spatially Distributed Firms," Computational Economics, Society for Computational Economics, vol. 42(4), pages 373-391, December.
  3. Kirchkamp, Oliver & Nagel, Rosemarie, 2007. "Naive learning and cooperation in network experiments," Games and Economic Behavior, Elsevier, vol. 58(2), pages 269-292, February.
  4. Jurjen Kamphorst & Gerard van der Laan, 2006. "Learning in a Local Interaction Hawk-Dove Game," Tinbergen Institute Discussion Papers 06-034/1, Tinbergen Institute.
  5. Juan Montoro-Pons & Francisco Garcia-Sobrecases, 2003. "A Computational Approach to the Collective Action Problem: Assessment of Alternative Learning Rules," Computational Economics, Society for Computational Economics, vol. 21(1), pages 137-151, February.
  6. Juan D. Montoro-Pons, 2000. "Collective Action, Free Riding And Evolution," Computing in Economics and Finance 2000 279, Society for Computational Economics.
  7. repec:dgr:uvatin:2006034 is not listed on IDEAS

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