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Cycling in a stochastic learning algorithm for normal form games

Citations

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Cited by:

  1. Hopkins, Ed, 1999. "A Note on Best Response Dynamics," Games and Economic Behavior, Elsevier, vol. 29(1-2), pages 138-150, October.
  2. Bervoets, Sebastian & Bravo, Mario & Faure, Mathieu, 2020. "Learning with minimal information in continuous games," Theoretical Economics, Econometric Society, vol. 15(4), November.
  3. Mengel, Friederike, 2012. "Learning across games," Games and Economic Behavior, Elsevier, vol. 74(2), pages 601-619.
  4. Mario Bravo & Mathieu Faure, 2013. "Reinforcement Learning with Restrictions on the Action Set," AMSE Working Papers 1335, Aix-Marseille School of Economics, France, revised 01 Jul 2013.
  5. Mertikopoulos, Panayotis & Sandholm, William H., 2018. "Riemannian game dynamics," Journal of Economic Theory, Elsevier, vol. 177(C), pages 315-364.
  6. Güth Werner & Kliemt Hartmut & Peleg Bezalel, 2000. "Co-evolution of Preferences and Information in Simple Games of Trust," German Economic Review, De Gruyter, vol. 1(1), pages 83-110, February.
  7. Ianni, Antonella, 2014. "Learning strict Nash equilibria through reinforcement," Journal of Mathematical Economics, Elsevier, vol. 50(C), pages 148-155.
  8. Possajennikov, A., 1997. "An Analysis of a Simple Reinforcement Dynamics : Learning to Play an "Egalitarian" Equilibrium," Discussion Paper 1997-19, Tilburg University, Center for Economic Research.
  9. Ed Hopkins, 2002. "Two Competing Models of How People Learn in Games," Econometrica, Econometric Society, vol. 70(6), pages 2141-2166, November.
  10. Max Keilbach, 1999. "Network Externalities and the Path Dependence of Markets: Will Bill Gates Make It?," Computing in Economics and Finance 1999 711, Society for Computational Economics.
  11. M. Keilbach & M. Posch, 1998. "Network Externalities and the Dynamics of Markets," Working Papers ir98089, International Institute for Applied Systems Analysis.
  12. Laslier, Jean-Francois & Topol, Richard & Walliser, Bernard, 2001. "A Behavioral Learning Process in Games," Games and Economic Behavior, Elsevier, vol. 37(2), pages 340-366, November.
  13. Izquierdo, Luis R. & Izquierdo, Segismundo S. & Gotts, Nicholas M. & Polhill, J. Gary, 2007. "Transient and asymptotic dynamics of reinforcement learning in games," Games and Economic Behavior, Elsevier, vol. 61(2), pages 259-276, November.
  14. Beggs, A.W., 2005. "On the convergence of reinforcement learning," Journal of Economic Theory, Elsevier, vol. 122(1), pages 1-36, May.
  15. Hopkins, Ed & Posch, Martin, 2005. "Attainability of boundary points under reinforcement learning," Games and Economic Behavior, Elsevier, vol. 53(1), pages 110-125, October.
  16. Cominetti, Roberto & Melo, Emerson & Sorin, Sylvain, 2010. "A payoff-based learning procedure and its application to traffic games," Games and Economic Behavior, Elsevier, vol. 70(1), pages 71-83, September.
  17. Alanyali, Murat, 2010. "A note on adjusted replicator dynamics in iterated games," Journal of Mathematical Economics, Elsevier, vol. 46(1), pages 86-98, January.
  18. Giovanni Dosi & Marco Faillo & Luigi Marengo, 2018. "Beyond "Bounded Rationality": Behaviours and Learning in Complex Evolving Worlds," LEM Papers Series 2018/26, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  19. Windrum, Paul, 1999. "Simulation models of technological innovation: A Review," Research Memorandum 005, Maastricht University, Maastricht Economic Research Institute on Innovation and Technology (MERIT).
  20. Ianni, A., 2002. "Reinforcement learning and the power law of practice: some analytical results," Discussion Paper Series In Economics And Econometrics 0203, Economics Division, School of Social Sciences, University of Southampton.
  21. Mario Bravo, 2016. "An Adjusted Payoff-Based Procedure for Normal Form Games," Mathematics of Operations Research, INFORMS, vol. 41(4), pages 1469-1483, November.
  22. Georgios Chasparis & Jeff Shamma & Anders Rantzer, 2015. "Nonconvergence to saddle boundary points under perturbed reinforcement learning," International Journal of Game Theory, Springer;Game Theory Society, vol. 44(3), pages 667-699, August.
  23. Panayotis Mertikopoulos & William H. Sandholm, 2016. "Learning in Games via Reinforcement and Regularization," Mathematics of Operations Research, INFORMS, vol. 41(4), pages 1297-1324, November.
  24. Darmon, Eric & Waldeck, Roger, 2005. "Convergence of reinforcement learning to Nash equilibrium: A search-market experiment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(1), pages 119-130.
  25. Roger Waldeck & Eric Darmon, 2006. "Can boundedly rational sellers learn to play Nash?," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 1(2), pages 147-169, November.
  26. Norman, Thomas W.L., 2023. "Pigouvian algorithmic platform design," Journal of Economic Behavior & Organization, Elsevier, vol. 212(C), pages 322-332.
  27. M. Posch & A. Pichler & K. Sigmund, 1998. "The Efficiency of Adapting Aspiration Levels," Working Papers ir98103, International Institute for Applied Systems Analysis.
  28. Antonio Cabrales & Walter Garcia Fontes, 2000. "Estimating learning models from experimental data," Economics Working Papers 501, Department of Economics and Business, Universitat Pompeu Fabra.
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