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Transient and asymptotic dynamics of reinforcement learning in games

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  • Izquierdo, Luis R.
  • Izquierdo, Segismundo S.
  • Gotts, Nicholas M.
  • Polhill, J. Gary

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  • 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.
  • Handle: RePEc:eee:gamebe:v:61:y:2007:i:2:p:259-276
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    References listed on IDEAS

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    19. 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.
    20. Hopkins, Ed & Posch, Martin, 2005. "Attainability of boundary points under reinforcement learning," Games and Economic Behavior, Elsevier, vol. 53(1), pages 110-125, October.
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    Cited by:

    1. Sung-youn Kim, 2012. "A model of political information-processing and learning cooperation in the repeated Prisoner’s Dilemma," Journal of Theoretical Politics, , vol. 24(1), pages 46-65, January.
    2. Schuster, Stephan, 2010. "Network Formation with Adaptive Agents," MPRA Paper 27388, University Library of Munich, Germany.
    3. José Manuel Galán & Luis R. Izquierdo & Segismundo S. Izquierdo & José Ignacio Santos & Ricardo del Olmo & Adolfo López-Paredes & Bruce Edmonds, 2009. "Errors and Artefacts in Agent-Based Modelling," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(1), pages 1-1.
    4. Heymann, D. & Kawamura, E. & Perazzo, R. & Zimmermann, M.G., 2014. "Behavioral heuristics and market patterns in a Bertrand–Edgeworth game," Journal of Economic Behavior & Organization, Elsevier, vol. 105(C), pages 124-139.
    5. Yu Zhang & Jason Leezer, 2010. "Simulating human-like decisions in a memory-based agent model," Computational and Mathematical Organization Theory, Springer, vol. 16(4), pages 373-399, December.
    6. Ianni, Antonella, 2014. "Learning strict Nash equilibria through reinforcement," Journal of Mathematical Economics, Elsevier, vol. 50(C), pages 148-155.
    7. Dridi, Slimane & Lehmann, Laurent, 2014. "On learning dynamics underlying the evolution of learning rules," Theoretical Population Biology, Elsevier, vol. 91(C), pages 20-36.
    8. Liangliang Chang & Zhipeng Zhang & Chengyi Xia, 2023. "Impact of Decision Feedback on Networked Evolutionary Game with Delays in Control Channel," Dynamic Games and Applications, Springer, vol. 13(3), pages 783-800, September.
    9. Wang, Xianjia & Yang, Zhipeng & Liu, Yanli & Chen, Guici, 2023. "A reinforcement learning-based strategy updating model for the cooperative evolution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 618(C).
    10. Xiaopeng Li & Zhonglin Wang & Jiuqiang Liu & Guihai Yu, 2023. "The Sense of Cooperation on Interdependent Networks Inspired by Influence-Based Self-Organization," Mathematics, MDPI, vol. 11(4), pages 1-16, February.
    11. Oyarzun, Carlos & Sarin, Rajiv, 2013. "Learning and risk aversion," Journal of Economic Theory, Elsevier, vol. 148(1), pages 196-225.
    12. Segismundo S. Izquierdo & Luis R. Izquierdo & Nicholas M. Gotts, 2008. "Reinforcement Learning Dynamics in Social Dilemmas," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(2), pages 1-1.
    13. Jia, Danyang & Li, Tong & Zhao, Yang & Zhang, Xiaoqin & Wang, Zhen, 2022. "Empty nodes affect conditional cooperation under reinforcement learning," Applied Mathematics and Computation, Elsevier, vol. 413(C).
    14. Schuster, Stephan, 2012. "Applications in Agent-Based Computational Economics," MPRA Paper 47201, University Library of Munich, Germany.

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