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Full-Text Articles in Social and Behavioral Sciences
Convergence In Models With Bounded Expected Relative Hazard Rates, Carlos Oyarzun, Johannes Ruf
Convergence In Models With Bounded Expected Relative Hazard Rates, Carlos Oyarzun, Johannes Ruf
Carlos Oyarzun
We provide a general framework to study stochastic sequences related to an array of models in different literatures, including models of individual learning in economics, learning automata in computer sciences, social learning in marketing, and many others. In this setup, we study the asymptotic properties of a class of stochastic sequences that take values in [0,1] and satisfy a property that we call “bounded expected relative hazard rates.” We provide sufficient conditions for related sequences, which, compared to the original sequence, either move slowly or slow down over time, that yield con- vergence to one with high probability or almost …
A Note On Absolutely Expedient Learning Rules, Carlos Oyarzun
A Note On Absolutely Expedient Learning Rules, Carlos Oyarzun
Carlos Oyarzun
I provide a full characterization of the set of absolutely expedient learning rules introduced in Börgers, Morales, and Sarin (2004) [“Expedient and monotone learning rules,” Econometrica, 72, 383–405]. The expected change in the expected payoff can be written as a quadratic form on the vector of relative expected payoffs of the strategies. This permits use of standard linear algebra arguments to provide a characterization in terms of the matrix defining this quadratic form.