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Citations for "Average Behavior in Learning Models"

by D. Canning

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  1. Apesteguia, Jose & Huck, Steffen & Oechssler, Jorg, 2007. "Imitation--theory and experimental evidence," Journal of Economic Theory, Elsevier, vol. 136(1), pages 217-235, September.
  2. Huw D. Dixon & Paolo Lupi, "undated". "Learning With a Known Average: a Simulation Study of Alternative Learning Rules," Computing in Economics and Finance 1997 154, Society for Computational Economics.
  3. Weibull, Jörgen W., 1992. "An Introduction to Evolutionary Game Theory," Working Paper Series 347, Research Institute of Industrial Economics.
  4. Kalai, Ehud & Lehrer, Ehud, 1993. "Rational Learning Leads to Nash Equilibrium," Econometrica, Econometric Society, vol. 61(5), pages 1019-1045, September.
  5. Dixon, Huw David, 2000. "Keeping up with the Joneses: competition and the evolution of collusion," Journal of Economic Behavior & Organization, Elsevier, vol. 43(2), pages 223-238, October.
  6. Paolo Lupi, 1998. "The Propagation of Cooperation in a Model of Learning with Endogenous Aspirations," Research in Economics 98-06-052e, Santa Fe Institute.
  7. Safarzynska, Karolina & van den Bergh, Jeroen C.J.M., 2011. "Beyond replicator dynamics: Innovation-selection dynamics and optimal diversity," Journal of Economic Behavior & Organization, Elsevier, vol. 78(3), pages 229-245, May.
  8. Karolina Safarzyńska & Jeroen Bergh, 2010. "Evolutionary models in economics: a survey of methods and building blocks," Journal of Evolutionary Economics, Springer, vol. 20(3), pages 329-373, June.
  9. Jacobsen, Hans Jorgen & Jensen, Mogens & Sloth, Birgitte, 2001. "Evolutionary Learning in Signalling Games," Games and Economic Behavior, Elsevier, vol. 34(1), pages 34-63, January.
  10. Goyal, Sanjeev & Vega-Redondo, Fernando, 2005. "Network formation and social coordination," Games and Economic Behavior, Elsevier, vol. 50(2), pages 178-207, February.
  11. Sobel, Joel, 2017. "A note on pre-play communication," Games and Economic Behavior, Elsevier, vol. 102(C), pages 477-486.
  12. Hopkins, Ed, 1999. "Learning, Matching, and Aggregation," Games and Economic Behavior, Elsevier, vol. 26(1), pages 79-110, January.
  13. William Tracy, 2014. "Paradox Lost: The Evolution of Strategies in Selten’s Chain Store Game," Computational Economics, Springer;Society for Computational Economics, vol. 43(1), pages 83-103, January.
  14. Goyal, S. & Vega-Redondo, F., 2000. "Learning, Network Formation and Coordination," Econometric Institute Research Papers EI 9954-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  15. Cabrales, Antonio & Garcia-Fontes, Walter & Motta, Massimo, 2000. "Risk dominance selects the leader: An experimental analysis," International Journal of Industrial Organization, Elsevier, vol. 18(1), pages 137-162, January.
  16. Anderlini, Luca, 1999. "Communication, Computability, and Common Interest Games," Games and Economic Behavior, Elsevier, vol. 27(1), pages 1-37, April.
  17. Blume, Lawrence E., 2003. "How noise matters," Games and Economic Behavior, Elsevier, vol. 44(2), pages 251-271, August.
  18. Karolina Safarzyńska & Jeroen Bergh, 2013. "An evolutionary model of energy transitions with interactive innovation-selection dynamics," Journal of Evolutionary Economics, Springer, vol. 23(2), pages 271-293, April.
  19. Dai, Darong, 2012. "On the existence and stability of Pareto optimal endogenous matching with fairness," MPRA Paper 40457, University Library of Munich, Germany.
  20. Dai, Darong, 2012. "Learning Nash Equilibria," MPRA Paper 40040, University Library of Munich, Germany.
  21. Ramsza, Michal & Seymour, Robert M., 2010. "Fictitious play in an evolutionary environment," Games and Economic Behavior, Elsevier, vol. 68(1), pages 303-324, January.
  22. Dai, Darong, 2012. "On the Existence and Stability of Pareto Optimal Endogenous Matching with Fairness," MPRA Paper 40560, University Library of Munich, Germany.
This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.