Minimax Play at Wimbledon*
* This paper has been replicatedAuthor
Abstract
Suggested Citation
Note: DOI: 10.1257/aer.91.5.1521
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- 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.
- Wooders, John & Shachat, Jason M., 2001. "On the Irrelevance of Risk Attitudes in Repeated Two-Outcome Games," Games and Economic Behavior, Elsevier, vol. 34(2), pages 342-363, February.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Van Essen, Matt & Wooders, John, 2015.
"Blind stealing: Experience and expertise in a mixed-strategy poker experiment,"
Games and Economic Behavior, Elsevier, vol. 91(C), pages 186-206.
- Matt Van Essen & John Wooders, 2013. "Blind Stealing: Experience and Expertise in a Mixed-Strategy Poker Experiment," Working Paper Series 6, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
- Scroggin, Steven, 2007. "Exploitable actions of believers in the "law of small numbers" in repeated constant-sum games," Journal of Economic Theory, Elsevier, vol. 133(1), pages 219-235, March.
- Ido Erev & Alvin Roth & Robert Slonim & Greg Barron, 2007. "Learning and equilibrium as useful approximations: Accuracy of prediction on randomly selected constant sum games," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 33(1), pages 29-51, October.
- Erev, Ido & Roth, Alvin E. & Slonim, Robert L. & Barron, Greg, 2002. "Predictive value and the usefulness of game theoretic models," International Journal of Forecasting, Elsevier, vol. 18(3), pages 359-368.
- Shachat, Jason M., 2002. "Mixed Strategy Play and the Minimax Hypothesis," Journal of Economic Theory, Elsevier, vol. 104(1), pages 189-226, May.
- Ido Erev & Alvin E. Roth & Robert Slonim, 2016. "Minimax across a population of games," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 2(2), pages 144-156, November.
- Haruvy, Ernan & Roth, Alvin E. & Unver, M. Utku, 2006.
"The dynamics of law clerk matching: An experimental and computational investigation of proposals for reform of the market,"
Journal of Economic Dynamics and Control, Elsevier, vol. 30(3), pages 457-486, March.
- Ernan Haruvy & Alvin E. Roth & M. Utku Unver, 2004. "The Dynamics of Law Clerk Matching: An Experimental and Computational Investigation of Proposals for Reform of the Market," Experimental 0404001, University Library of Munich, Germany.
- Novarese, Marco & Lanteri, Alessandro & Tibaldeschi, Cesare, 2010. "Learning, Generalization and the Perception of Information: an Experimental Study," MPRA Paper 28007, University Library of Munich, Germany.
- Todd Guilfoos & Andreas Duus Pape, 2020. "Estimating Case-Based Learning," Games, MDPI, vol. 11(3), pages 1-25, September.
- Tian, Ye & Chiu, Yi-Chang & Sun, Jian, 2019. "Understanding behavioral effects of tradable mobility credit scheme: An experimental economics approach," Transport Policy, Elsevier, vol. 81(C), pages 1-11.
- Noah Gans & George Knox & Rachel Croson, 2007. "Simple Models of Discrete Choice and Their Performance in Bandit Experiments," Manufacturing & Service Operations Management, INFORMS, vol. 9(4), pages 383-408, December.
- Atanasios Mitropoulos, 2001. "Learning Under Little Information: An Experiment on Mutual Fate Control," Game Theory and Information 0110003, University Library of Munich, Germany.
- Terry E. Daniel & Eyran J. Gisches & Amnon Rapoport, 2009. "Departure Times in Y-Shaped Traffic Networks with Multiple Bottlenecks," American Economic Review, American Economic Association, vol. 99(5), pages 2149-2176, December.
- Iftekhar, M. S. & Tisdell, J. G., 2018. "Learning in repeated multiple unit combinatorial auctions: An experimental study," Working Papers 267301, University of Western Australia, School of Agricultural and Resource Economics.
- Stahl, Dale O., 2001. "Population rule learning in symmetric normal-form games: theory and evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 45(1), pages 19-35, May.
- Brenner, Thomas & Witt, Ulrich, 2003. "Melioration learning in games with constant and frequency-dependent pay-offs," Journal of Economic Behavior & Organization, Elsevier, vol. 50(4), pages 429-448, April.
- Paolo Crosetto & Alexia Gaudeul, 2014.
"Choosing whether to compete: Price and format competition with consumer confusion,"
Jena Economic Research Papers
2014-026, Friedrich-Schiller-University Jena.
- Gaudeul, Alexia & Crosetto, Paolo, 2016. "Choosing whether to compete: Price and format competition with consumer confusion," VfS Annual Conference 2016 (Augsburg): Demographic Change 145875, Verein für Socialpolitik / German Economic Association.
- Crosetto, P. & Gaudeul, A., 2014. "Choosing whether to compete: Price and format competition with consumer confusion," Working Papers 2014-08, Grenoble Applied Economics Laboratory (GAEL).
- Dürsch, Peter & Kolb, Albert & Oechssler, Jörg & Schipper, Burkhard, 2005.
"Rage against the machines : how subjects learn to play against computers,"
Papers
05-36, Sonderforschungsbreich 504.
- Dürsch, Peter & Kolb, Albert & Oechssler, Jörg & Schipper, Burkhard C., 2005. "Rage Against the Machines: How Subjects Learn to Play Against Computers," Discussion Paper Series of SFB/TR 15 Governance and the Efficiency of Economic Systems 63, Free University of Berlin, Humboldt University of Berlin, University of Bonn, University of Mannheim, University of Munich.
- Dürsch, Peter & Kolb, Albert & Oechssler, Jörg & Schipper, Burkhard, 2005. "Rage Against the Machines - How Subjects Learn to Play Against Computers," Sonderforschungsbereich 504 Publications 05-36, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
- Peter Dürsch & Albert Kolb & Jörg Oechssler & Burkhard C. Schipper, 2005. "Rage Against the Machines: How Subjects Learn to Play Against Computers," Working Papers 0423, University of Heidelberg, Department of Economics, revised Oct 2005.
- Burkhard C. Schipper & Jörg Oechssler & Albert Kolb, 2005. "Rage Against the Machines: How Subjects Learn to Play Against Computers," Working Papers 323, University of California, Davis, Department of Economics.
- Peter Duersch & Albert Kolb & Joerg Oechssler & Burkhard Schipper, 2005. "Rage Against the Machines: How Subjects Learn to Play Against Computers," Game Theory and Information 0510012, University Library of Munich, Germany.
- Dürsch, Peter & Kolb, Albert & Oechssler, Jörg & Schipper, Burkhard C., 2005. "Rage Against the Machines: How Subjects Learn to Play Against Computers," Bonn Econ Discussion Papers 31/2005, University of Bonn, Bonn Graduate School of Economics (BGSE).
- Asim Ansari & Ricardo Montoya & Oded Netzer, 2012. "Dynamic learning in behavioral games: A hidden Markov mixture of experts approach," Quantitative Marketing and Economics (QME), Springer, vol. 10(4), pages 475-503, December.
- Ianni, A., 2002. "Reinforcement learning and the power law of practice: some analytical results," Discussion Paper Series In Economics And Econometrics 203, Economics Division, School of Social Sciences, University of Southampton.
Replication
This item has been replicated by:More about this item
JEL classification:
- C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
- L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism
Lists
This item is featured on the following reading lists, Wikipedia, or ReplicationWiki pages:- Minimax Play at Wimbledon (AER 2001) in ReplicationWiki
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aea:aecrev:v:91:y:2001:i:5:p:1521-1538. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://edirc.repec.org/data/aeaaaea.html .
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Michael P. Albert (email available below). General contact details of provider: https://edirc.repec.org/data/aeaaaea.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.