We examine an evolutionary model in which the primary source of "noise" that moves the model between equilibria is not random, arbitrarily improbable mutations but mistakes in learning. We find conditions under which the payoff-dominant equilibrium in a 2x2 game is selected by the model as well as conditions under which the risk- dominant equilibrium is selected. The relevant risk-dominance considerations, however, arise not in the original game but in a "fitness game" derived from the process by which payoffs in the original game are translated into evolutionary fitnesses. We also find that waiting times until the limiting distribution is reached can be shorter than in a mutation-driven model. To explore the robustness of the results to the specification of the model, we present a number of comparative static results as well as a "two-tiered" evolutionary model in which the rules by which agents learn to play the game are themselves subject to evolutionary pressure.
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Paper provided by University of Bonn, Germany in its series Discussion Paper Serie B with number
275.
Length: pages Date of creation: Feb 1994 Date of revision: Handle: RePEc:bon:bonsfb:275
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Find related papers by JEL classification: C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General
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Carlsson, Hans & van Damme, Eric, 1993.
"Global Games and Equilibrium Selection,"
Econometrica,
Econometric Society, vol. 61(5), pages 989-1018, September.
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Other versions:
Itzhak Gilboa & David Schmeidler, 1993.
"Case-Based Optimization,"
Discussion Papers
1039, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
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