A payoff-based learning procedure and its application to traffic games
AbstractA stochastic process that describes a payoff-based learning procedure and the associated adaptive behavior of players in a repeated game is considered. The process is shown to converge almost surely towards a stationary state which is characterized as an equilibrium for a related game. The analysis is based on techniques borrowed from the theory of stochastic algorithms and proceeds by studying an associated continuous dynamical system which represents the evolution of the players' evaluations. An application to the case of finitely many users in a congested traffic network with parallel links is considered. Alternative descriptions for the dynamics and the corresponding rest points are discussed, including a Lagrangian representation.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Elsevier in its journal Games and Economic Behavior.
Volume (Year): 70 (2010)
Issue (Month): 1 (September)
Contact details of provider:
Web page: http://www.elsevier.com/locate/inca/622836
Games Learning Adaptive dynamics Stochastic algorithms Congestion games;
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Drew Fudenberg & David K. Levine, 1998.
"The Theory of Learning in Games,"
MIT Press Books,
The MIT Press,
edition 1, volume 1, number 0262061945, June.
- Sergiu Hart, 2005.
Econometric Society, vol. 73(5), pages 1401-1430, 09.
- Michel Benaïm & Josef Hofbauer & Sylvain Sorin, 2005. "Stochastic Approximations and Differential Inclusions; Part II: Applications," Working Papers hal-00242974, HAL.
- John Duffy & Ed Hopkins, 2004.
"Learning, Information and Sorting in Market Entry Games: Theory and Evidence,"
ESE Discussion Papers
78, Edinburgh School of Economics, University of Edinburgh.
- Duffy, John & Hopkins, Ed, 2005. "Learning, information, and sorting in market entry games: theory and evidence," Games and Economic Behavior, Elsevier, vol. 51(1), pages 31-62, April.
- John Duffy & Ed Hopkins, 2010. "Learning, Information and Sorting in Market Entry Games: Theory and Evidence," Levine's Working Paper Archive 506439000000000355, David K. Levine.
- Arthur, W Brian, 1993. "On Designing Economic Agents That Behave Like Human Agents," Journal of Evolutionary Economics, Springer, vol. 3(1), pages 1-22, February.
- Sandholm, William H, 2002. "Evolutionary Implementation and Congestion Pricing," Review of Economic Studies, Wiley Blackwell, vol. 69(3), pages 667-89, July.
- Cascetta, Ennio, 1989. "A stochastic process approach to the analysis of temporal dynamics in transportation networks," Transportation Research Part B: Methodological, Elsevier, vol. 23(1), pages 1-17, February.
- Sandholm, William H., 2001. "Potential Games with Continuous Player Sets," Journal of Economic Theory, Elsevier, vol. 97(1), pages 81-108, March.
- Erel Avineri & Joseph Prashker, 2006. "The Impact of Travel Time Information on Travelers’ Learning under Uncertainty," Transportation, Springer, vol. 33(4), pages 393-408, 07.
- Freund, Yoav & Schapire, Robert E., 1999. "Adaptive Game Playing Using Multiplicative Weights," Games and Economic Behavior, Elsevier, vol. 29(1-2), pages 79-103, October.
- Josef Hofbauer & William H. Sandholm, 2002. "On the Global Convergence of Stochastic Fictitious Play," Econometrica, Econometric Society, vol. 70(6), pages 2265-2294, November.
- Alan Beggs, 2002.
"On the Convergence of Reinforcement Learning,"
Economics Series Working Papers
96, University of Oxford, Department of Economics.
- Michel Benaim & Josef Hofbauer & Sylvain Sorin, 2005. "Stochastic Approximations and Differential Inclusions II: Applications," Levine's Bibliography 784828000000000098, UCLA Department of Economics.
- Monderer, Dov & Shapley, Lloyd S., 1996. "Potential Games," Games and Economic Behavior, Elsevier, vol. 14(1), pages 124-143, May.
- T. Borgers & R. Sarin, 2010.
"Learning Through Reinforcement and Replicator Dynamics,"
Levine's Working Paper Archive
380, David K. Levine.
- Borgers, Tilman & Sarin, Rajiv, 1997. "Learning Through Reinforcement and Replicator Dynamics," Journal of Economic Theory, Elsevier, vol. 77(1), pages 1-14, November.
- Tilman B�rgers & Rajiv Sarin, . "Learning Through Reinforcement and Replicator Dynamics," ELSE working papers 051, ESRC Centre on Economics Learning and Social Evolution.
- Benaim, Michel & Hirsch, Morris W., 1999. "Mixed Equilibria and Dynamical Systems Arising from Fictitious Play in Perturbed Games," Games and Economic Behavior, Elsevier, vol. 29(1-2), pages 36-72, October.
- Martin Posch, 1997. "Cycling in a stochastic learning algorithm for normal form games," Journal of Evolutionary Economics, Springer, vol. 7(2), pages 193-207.
- Foster, Dean P. & Vohra, Rakesh V., 1997. "Calibrated Learning and Correlated Equilibrium," Games and Economic Behavior, Elsevier, vol. 21(1-2), pages 40-55, October.
- J.-F. Laslier & R. Topol & B. Walliser, 1999.
"A behavioral learning process in games,"
THEMA Working Papers
99-03, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
- Horowitz, Joel L., 1984. "The stability of stochastic equilibrium in a two-link transportation network," Transportation Research Part B: Methodological, Elsevier, vol. 18(1), pages 13-28, February.
- Young, H. Peyton, 2004. "Strategic Learning and its Limits," OUP Catalogue, Oxford University Press, number 9780199269181.
- Selten, R. & Chmura, T. & Pitz, T. & Kube, S. & Schreckenberg, M., 2007. "Commuters route choice behaviour," Games and Economic Behavior, Elsevier, vol. 58(2), pages 394-406, February.
- 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 848-81, September.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wendy Shamier).
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 references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.