Reinforcement learning in a prisoner's dilemma
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DOI: 10.1016/j.geb.2024.01.004
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- Calvano, Emilio & Calzolari, Giacomo & Denicolò, Vincenzo & Pastorello, Sergio, 2023. "Algorithmic collusion: Genuine or spurious?," International Journal of Industrial Organization, Elsevier, vol. 90(C).
- Glenn Ellison, 2000. "Basins of Attraction, Long-Run Stochastic Stability, and the Speed of Step-by-Step Evolution," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 67(1), pages 17-45.
- Jonathan Newton, 2018. "Evolutionary Game Theory: A Renaissance," Games, MDPI, vol. 9(2), pages 1-67, May.
- Erev, Ido & Roth, Alvin E, 1998. "Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria," American Economic Review, American Economic Association, vol. 88(4), pages 848-881, September.
- Heinrich H. Nax, 2019. "Uncoupled Aspiration Adaptation Dynamics Into the Core," German Economic Review, Verein für Socialpolitik, vol. 20(2), pages 243-256, May.
- Newton, Jonathan & Sawa, Ryoji, 2015.
"A one-shot deviation principle for stability in matching problems,"
Journal of Economic Theory, Elsevier, vol. 157(C), pages 1-27.
- Newton, Jonathan & Sawa, Ryoji, 2013. "A one-shot deviation principle for stability in matching problems," Working Papers 2013-09, University of Sydney, School of Economics, revised Jul 2014.
- Calzolari, Giacomo & Calvano, Emilio & Denicolo, Vincenzo & Pastorello, Sergio, 2021. "Algorithmic collusion with imperfect monitoring," CEPR Discussion Papers 15738, C.E.P.R. Discussion Papers.
- Arnoud V. den Boer & Janusz M. Meylahn & Maarten Pieter Schinkel, 2022. "Artificial Collusion: Examining Supracompetitive Pricing by Q-learning Algorithms," Tinbergen Institute Discussion Papers 22-067/VII, Tinbergen Institute.
- Ennio Bilancini & Leonardo Boncinelli, 2020.
"The evolution of conventions under condition-dependent mistakes,"
Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 69(2), pages 497-521, March.
- Ennio Bilancini & Leonardo Boncinelli, 2016. "The Evolution of Conventions under Condition-Dependent Mistakes," Working Papers - Economics wp2016_11.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
- Matthias Hettich, 2021. "Algorithmic Collusion: Insights from Deep Learning," CQE Working Papers 9421, Center for Quantitative Economics (CQE), University of Muenster.
- Stephanie Assad & Robert Clark & Daniel Ershov & Lei Xu, 2022. "Identifying Algorithmic Pricing Technology Adoption in Retail Gasoline Markets," AEA Papers and Proceedings, American Economic Association, vol. 112, pages 457-460, May.
- Young, H Peyton, 1993. "The Evolution of Conventions," Econometrica, Econometric Society, vol. 61(1), pages 57-84, January.
- Sergiu Hart & Andreu Mas-Colell, 2013.
"Uncoupled Dynamics Do Not Lead To Nash Equilibrium,"
World Scientific Book Chapters, in: Simple Adaptive Strategies From Regret-Matching to Uncoupled Dynamics, chapter 7, pages 153-163,
World Scientific Publishing Co. Pte. Ltd..
- Sergiu Hart & Andreu Mas-Colell, 2003. "Uncoupled Dynamics Do Not Lead to Nash Equilibrium," American Economic Review, American Economic Association, vol. 93(5), pages 1830-1836, December.
- Roth, Alvin E. & Erev, Ido, 1995. "Learning in extensive-form games: Experimental data and simple dynamic models in the intermediate term," Games and Economic Behavior, Elsevier, vol. 8(1), pages 164-212.
- Emilio Calvano & Giacomo Calzolari & Vincenzo Denicolò & Sergio Pastorello, 2020.
"Artificial Intelligence, Algorithmic Pricing, and Collusion,"
American Economic Review, American Economic Association, vol. 110(10), pages 3267-3297, October.
- Calzolari, Giacomo & Calvano, Emilio & Denicolo, Vincenzo & Pastorello, Sergio, 2018. "Artificial intelligence, algorithmic pricing and collusion," CEPR Discussion Papers 13405, C.E.P.R. Discussion Papers.
- Milgrom, Paul & Roberts, John, 1990. "Rationalizability, Learning, and Equilibrium in Games with Strategic Complementarities," Econometrica, Econometric Society, vol. 58(6), pages 1255-1277, November.
- Matthias Blonski & Peter Ockenfels & Giancarlo Spagnolo, 2011. "Equilibrium Selection in the Repeated Prisoner's Dilemma: Axiomatic Approach and Experimental Evidence," American Economic Journal: Microeconomics, American Economic Association, vol. 3(3), pages 164-192, August.
- , P. & , Peyton, 2006. "Regret testing: learning to play Nash equilibrium without knowing you have an opponent," Theoretical Economics, Econometric Society, vol. 1(3), pages 341-367, September.
- Waltman, Ludo & Kaymak, Uzay, 2008. "Q-learning agents in a Cournot oligopoly model," Journal of Economic Dynamics and Control, Elsevier, vol. 32(10), pages 3275-3293, October.
- Mengel, Friederike, 2014.
"Learning by (limited) forward looking players,"
Journal of Economic Behavior & Organization, Elsevier, vol. 108(C), pages 59-77.
- Mengel, F., 2008. "Learning by (limited) forward looking players," Research Memorandum 053, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
- Heinrich Nax & Bary Pradelski, 2015. "Evolutionary dynamics and equitable core selection in assignment games," International Journal of Game Theory, Springer;Game Theory Society, vol. 44(4), pages 903-932, November.
- John Asker & Chaim Fershtman & Ariel Pakes, 2021.
"Artificial Intelligence and Pricing: The Impact of Algorithm Design,"
NBER Working Papers
28535, National Bureau of Economic Research, Inc.
- Fershtman, Chaim & Asker, John & Pakes, Ariel, 2021. "Artificial intelligence and Pricing: The Impact of Algorithm Design," CEPR Discussion Papers 15880, C.E.P.R. Discussion Papers.
- John Asker & Chaim Fershtman & Ariel Pakes, 2022. "Artificial Intelligence, Algorithm Design, and Pricing," AEA Papers and Proceedings, American Economic Association, vol. 112, pages 452-456, May.
- Bilancini, Ennio & Boncinelli, Leonardo & Nax, Heinrich H., 2021. "What noise matters? Experimental evidence for stochastic deviations in social norms," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 90(C).
- Joseph E Harrington, 2018. "Developing Competition Law For Collusion By Autonomous Artificial Agents," Journal of Competition Law and Economics, Oxford University Press, vol. 14(3), pages 331-363.
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Cited by:
- Zhang Xu & Wei Zhao, 2024. "On Mechanism Underlying Algorithmic Collusion," Papers 2409.01147, arXiv.org.
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More about this item
Keywords
Q-learning; Stochastic stability; Evolutionary game theory; Collusion; Pricing-algorithms;All these keywords.
JEL classification:
- C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
- C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
- D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection
- D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
- L41 - Industrial Organization - - Antitrust Issues and Policies - - - Monopolization; Horizontal Anticompetitive Practices
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