We define Player-Compatible Equilibrium or "PCE," which imposes cross-player restrictions on magnitudes of the players' "trembles" onto different actions . These restrictions are inspired by the idea that trembles correspond to deliberate experiments by inexperienced agents who are unsure of the prevailing distribution of strategies in opponent populations  . We show that PCE selects the "intuitive" equilibria in a number of examples where trembling-hand perfect equilibrium (Selten, 1975) and proper equilibrium (Myerson, 1978) have no bite. We also provide a learning-based microfoundation for PCE in some easy-to-analyze classes of games . Finally, we conduct a lab experiment based on one of our examples and verify PCE leads to better predictions than other equilibrium concepts.
We define Player-Compatible Equilibrium or "PCE," which imposes cross-player restrictions on magnitudes of the players' "trembles" onto different strategies . These restrictions are inspired by the idea that trembles correspond to deliberate experiments by inexperienced agents who are unsure of the prevailing distribution of play in opponent populations , and that different players' relative "compatibilities" with various strategies determine the relative frequencies of their experiments . We show that PCE selects the "intuitive" equilibria in a number of examples where trembling-hand perfect equilibrium (Selten, 1975) and proper equilibrium (Myerson, 1978) have no bite. We also provide learning-based microfoundations for our cross-player tremble restrictions in a class of games using three different specifications of how agents handle the exploration/exploitation trade-off: expected utility maximization, Bayesian upper confidence bounds, and Thompson sampling . Finally, we conduct a lab experiment based on one of our examples and verify PCE leads to better predictions than other equilibrium concepts.
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, and that different players' relative "compatibilities" with various strategies determine the relative frequencies of their experiments
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microfoundation for PCE in some easy-to-analyze classes of games
microfoundations for our cross-player tremble restrictions in a class of games using three different specifications of how agents handle the exploration/exploitation trade-off: expected utility maximization, Bayesian upper confidence bounds, and Thompson sampling