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On the Convergence of Reinforcement Learning

Citations

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Cited by:

  1. Beggs, Alan, 2022. "Reference points and learning," Journal of Mathematical Economics, Elsevier, vol. 100(C).
  2. Maxwell Pak & Bing Xu, 2016. "Generalized reinforcement learning in perfect-information games," International Journal of Game Theory, Springer;Game Theory Society, vol. 45(4), pages 985-1011, November.
  3. Friedman, Daniel & Huck, Steffen & Oprea, Ryan & Weidenholzer, Simon, 2015. "From imitation to collusion: Long-run learning in a low-information environment," Journal of Economic Theory, Elsevier, vol. 155(C), pages 185-205.
  4. Hofbauer, Josef & Hopkins, Ed, 2005. "Learning in perturbed asymmetric games," Games and Economic Behavior, Elsevier, vol. 52(1), pages 133-152, July.
  5. Josephson, Jens, 2008. "A numerical analysis of the evolutionary stability of learning rules," Journal of Economic Dynamics and Control, Elsevier, vol. 32(5), pages 1569-1599, May.
  6. Köke, Sonja & Lange, Andreas & Nicklisch, Andreas, 2015. "Adversity is a school of wisdomː Experimental evidence on cooperative protection against stochastic losses," WiSo-HH Working Paper Series 22, University of Hamburg, Faculty of Business, Economics and Social Sciences, WISO Research Laboratory.
  7. 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.
  8. Ding, Jieyao & Nicklisch, Andreas, 2013. "On the impulse in impulse learning," Economics Letters, Elsevier, vol. 121(2), pages 294-297.
  9. Nicklisch, Andreas & Köke, Sonja & Lange, Andreas, 2016. "Is Adversity a School of Wisdom? Experimental Evidence on Cooperative Protection Against Stochastic Losses," VfS Annual Conference 2016 (Augsburg): Demographic Change 145716, Verein für Socialpolitik / German Economic Association.
  10. Jacques Durieu & Philippe Solal, 2012. "Models of Adaptive Learning in Game Theory," Chapters, in: Richard Arena & Agnès Festré & Nathalie Lazaric (ed.), Handbook of Knowledge and Economics, chapter 11, Edward Elgar Publishing.
  11. Chmura, Thorsten & Goerg, Sebastian J. & Selten, Reinhard, 2012. "Learning in experimental 2×2 games," Games and Economic Behavior, Elsevier, vol. 76(1), pages 44-73.
  12. Naoki Funai, 2013. "An Adaptive Learning Model in Coordination Games," Discussion Papers 13-14, Department of Economics, University of Birmingham.
  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. Jieyao Ding & Andreas Nicklisch, 2013. "On the Impulse in Impulse Learning," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2013_02, Max Planck Institute for Research on Collective Goods.
  15. Chernov, G. & Susin, I., 2019. "Models of learning in games: An overview," Journal of the New Economic Association, New Economic Association, vol. 44(4), pages 77-125.
  16. Schuster, Stephan, 2010. "Network Formation with Adaptive Agents," MPRA Paper 27388, University Library of Munich, Germany.
  17. Mele, Antonio & Molnár, Krisztina & Santoro, Sergio, 2020. "On the perils of stabilizing prices when agents are learning," Journal of Monetary Economics, Elsevier, vol. 115(C), pages 339-353.
  18. Hopkins, Ed & Posch, Martin, 2005. "Attainability of boundary points under reinforcement learning," Games and Economic Behavior, Elsevier, vol. 53(1), pages 110-125, October.
  19. 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.
  20. Han, Jungsuk & Sangiorgi, Francesco, 2018. "Searching for information," Journal of Economic Theory, Elsevier, vol. 175(C), pages 342-373.
  21. repec:esx:essedp:715 is not listed on IDEAS
  22. Alanyali, Murat, 2010. "A note on adjusted replicator dynamics in iterated games," Journal of Mathematical Economics, Elsevier, vol. 46(1), pages 86-98, January.
  23. Ianni, Antonella, 2014. "Learning strict Nash equilibria through reinforcement," Journal of Mathematical Economics, Elsevier, vol. 50(C), pages 148-155.
  24. Jaspersen, Johannes G. & Montibeller, Gilberto, 2020. "On the learning patterns and adaptive behavior of terrorist organizations," European Journal of Operational Research, Elsevier, vol. 282(1), pages 221-234.
  25. Albert Banal-Estañol & Augusto Rupérez Micola, 2009. "Composition of Electricity Generation Portfolios, Pivotal Dynamics, and Market Prices," Management Science, INFORMS, vol. 55(11), pages 1813-1831, November.
  26. Conor Mayo-Wilson & Kevin Zollman & David Danks, 2013. "Wisdom of crowds versus groupthink: learning in groups and in isolation," International Journal of Game Theory, Springer;Game Theory Society, vol. 42(3), pages 695-723, August.
  27. Fortini, Sandra & Petrone, Sonia & Sporysheva, Polina, 2018. "On a notion of partially conditionally identically distributed sequences," Stochastic Processes and their Applications, Elsevier, vol. 128(3), pages 819-846.
  28. Oyarzun, Carlos & Ruf, Johannes, 2014. "Convergence in models with bounded expected relative hazard rates," Journal of Economic Theory, Elsevier, vol. 154(C), pages 229-244.
  29. Naoki Funai, 2019. "Convergence results on stochastic adaptive learning," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 68(4), pages 907-934, November.
  30. March, Christoph, 2019. "The behavioral economics of artificial intelligence: Lessons from experiments with computer players," BERG Working Paper Series 154, Bamberg University, Bamberg Economic Research Group.
  31. Manxi Wu & Saurabh Amin & Asuman Ozdaglar, 2021. "Multi-agent Bayesian Learning with Best Response Dynamics: Convergence and Stability," Papers 2109.00719, arXiv.org.
  32. Naoki Funai, 2013. "An Adaptive Learning Model in Coordination Games," Games, MDPI, vol. 4(4), pages 1-22, November.
  33. Jonathan Newton, 2018. "Evolutionary Game Theory: A Renaissance," Games, MDPI, vol. 9(2), pages 1-67, May.
  34. Oyarzun, Carlos & Sarin, Rajiv, 2013. "Learning and risk aversion," Journal of Economic Theory, Elsevier, vol. 148(1), pages 196-225.
  35. March, Christoph, 2021. "Strategic interactions between humans and artificial intelligence: Lessons from experiments with computer players," Journal of Economic Psychology, Elsevier, vol. 87(C).
  36. Michael Foley & Rory Smead & Patrick Forber & Christoph Riedl, 2021. "Avoiding the bullies: The resilience of cooperation among unequals," PLOS Computational Biology, Public Library of Science, vol. 17(4), pages 1-18, April.
  37. Ilaria Brunetti & Yezekael Hayel & Eitan Altman, 2018. "State-Policy Dynamics in Evolutionary Games," Dynamic Games and Applications, Springer, vol. 8(1), pages 93-116, March.
  38. Manxi Wu & Saurabh Amin, 2019. "Securing Infrastructure Facilities: When Does Proactive Defense Help?," Dynamic Games and Applications, Springer, vol. 9(4), pages 984-1025, December.
  39. Funai, Naoki, 2022. "Reinforcement learning with foregone payoff information in normal form games," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 638-660.
  40. Nazaria Solferino & Viviana Solferino & Serena F. Taurino, 2018. "The economics analysis of a Q-learning model of cooperation with punishment and risk taking preferences," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(3), pages 601-613, October.
  41. Mario Bravo, 2016. "An Adjusted Payoff-Based Procedure for Normal Form Games," Mathematics of Operations Research, INFORMS, vol. 41(4), pages 1469-1483, November.
  42. 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.
  43. 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.
  44. Erik Mohlin & Robert Ostling & Joseph Tao-yi Wang, 2014. "Learning by Imitation in Games: Theory, Field, and Laboratory," Economics Series Working Papers 734, University of Oxford, Department of Economics.
  45. 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.
  46. Leslie, David S. & Collins, E.J., 2006. "Generalised weakened fictitious play," Games and Economic Behavior, Elsevier, vol. 56(2), pages 285-298, August.
  47. Giacomo Aletti & Caterina May & Piercesare Secchi, 2012. "A Functional Equation Whose Unknown is $\mathcal{P}([0,1])$ Valued," Journal of Theoretical Probability, Springer, vol. 25(4), pages 1207-1232, December.
  48. Kuang Xu & Se-Young Yun, 2020. "Reinforcement with Fading Memories," Mathematics of Operations Research, INFORMS, vol. 45(4), pages 1258-1288, November.
  49. Pemantle, Robin & Skyrms, Brian, 2004. "Network formation by reinforcement learning: the long and medium run," Mathematical Social Sciences, Elsevier, vol. 48(3), pages 315-327, November.
  50. Georgios Chasparis & Jeff Shamma, 2012. "Distributed Dynamic Reinforcement of Efficient Outcomes in Multiagent Coordination and Network Formation," Dynamic Games and Applications, Springer, vol. 2(1), pages 18-50, March.
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