Expedient and Monotone Learning Rules
This paper considers learning rules for environments in which little prior and feedback information is available to the decision-maker. Two properties of such learning rules, absolute expediency and monotonicity, are studied. The paper provides some necessary and some sufficient conditions for these properties. A number of examples show that there is quite a large variety of learning rules which have these properties. It is also shown that all learning rules that have these properties are, in some sense, related to replicator dynamics of evolutionary game theory.
|Date of creation:||2001|
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- Tilman B�rgers & Rajiv Sarin, .
"Learning Through Reinforcement and Replicator Dynamics,"
ELSE working papers
051, ESRC Centre on Economics Learning and Social Evolution.
- Borgers, Tilman & Sarin, Rajiv, 1997. "Learning Through Reinforcement and Replicator Dynamics," Journal of Economic Theory, Elsevier, vol. 77(1), pages 1-14, November.
- T. Borgers & R. Sarin, 2010. "Learning Through Reinforcement and Replicator Dynamics," Levine's Working Paper Archive 380, David K. Levine.
- David Easley & Aldo Rustichini, 1999. "Choice without Beliefs," Econometrica, Econometric Society, vol. 67(5), pages 1157-1184, September.
- Drew Fudenberg & David K. Levine, 1998.
"Learning in Games,"
Levine's Working Paper Archive
2222, David K. Levine.
- 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.
- T. Borgers & R. Sarin, 2010.
"Naïve Reinforcement Learning With Endogenous Aspirations,"
Levine's Working Paper Archive
381, David K. Levine.
- Borgers, Tilman & Sarin, Rajiv, 2000. "Naive Reinforcement Learning with Endogenous Aspirations," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 41(4), pages 921-50, November.
- Tilman B�rgers & Rajiv Sarin, . "Naive Reinforcement Learning With Endogenous Aspiration," ELSE working papers 037, ESRC Centre on Economics Learning and Social Evolution.
- Samuelson, L. & Zhang, J., 1991.
"Evolutionary Stability in Asymmetric Games,"
9132, Tilburg - Center for Economic Research.
- 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.
- Cross, John G, 1973. "A Stochastic Learning Model of Economic Behavior," The Quarterly Journal of Economics, MIT Press, vol. 87(2), pages 239-66, May.
- Rustichini, Aldo, 1999. "Optimal Properties of Stimulus--Response Learning Models," Games and Economic Behavior, Elsevier, vol. 29(1-2), pages 244-273, October.
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