Evolutionary Learning in Signalling Games
We study equilibrium selection by evolutionary learning in monotone signalling games. The learning process is a development of that introduced by Young for static games extended to deal with incomplete information and sequential moves; it thus involves stochastic trembles. For vanishing trembles the process gives rise to strong selection among sequential moves equilibria. If the game has separating equilibria, then in the long run only play according to a specific separating equilibrium, the so-called Riley equilibrium, will be observed frequently. This selection, is stronger than, and only partly in accordance with, traditional selection based on restrictions on "out-of-equilibrium" beliefs.
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