No-regret dynamics and fictitious play
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DOI: 10.1016/j.jet.2012.07.003
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- Yannick Viossat & Andriy Zapechelnyuk, 2013. "No-regret Dynamics and Fictitious Play," Post-Print hal-00713871, HAL.
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- Ewerhart, Christian & Valkanova, Kremena, 2020.
"Fictitious play in networks,"
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- Christian Ewerhart & Kremena Valkanova, 2016. "Fictitious play in networks," ECON - Working Papers 239, Department of Economics - University of Zurich, revised Jun 2019.
- Michael Nwogugu, 2020. "Regret Theory And Asset Pricing Anomalies In Incomplete Markets With Dynamic Un-Aggregated Preferences," Papers 2005.01709, arXiv.org.
- Christoph Graf & Viktor Zobernig & Johannes Schmidt & Claude Klöckl, 2024. "Computational Performance of Deep Reinforcement Learning to Find Nash Equilibria," Computational Economics, Springer;Society for Computational Economics, vol. 63(2), pages 529-576, February.
- 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.
- Leslie, David S. & Perkins, Steven & Xu, Zibo, 2020. "Best-response dynamics in zero-sum stochastic games," Journal of Economic Theory, Elsevier, vol. 189(C).
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More about this item
Keywords
Regret minimization; No-regret strategy; Fictitious play; Best-reply dynamics; Nash equilibrium; Hannan set; Curb set;All these keywords.
JEL classification:
- C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
- D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
- D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
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