Abstract:The effect of population heterogeneity in multi-agent learning is practically relevant but remains far from being well-understood. Motivated by this, we introduce a model of multi-population learning that allows for heterogeneous beliefs within each population and where agents respond to their beliefs via smooth fictitious play (SFP). We show that the system state -a probability distribution over beliefs -evolves according to a system of partial differential equations. We establish the convergence of SFP to Qu… Show more
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