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We collect, survey and develop methods of (one-dimensional) stochastic approximation in a framework that seems suitable to handle fairly broad generalizations of Polya urns.
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R. Argiento, R. Pemantle, B. Skyrms, S. Volkov: Learning to signal: analysis of a micro-level reinforcement model . Preprint (2008), 19 pages. To appear in Stoch. Proc. Appl
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I. Higueras, J. Moler, F. Plo, M. San Miguel: Urn models and differential algebraic equations . J. Appl. Probab., 40
2003
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S. Janson: Functional limit theorems for multitype branching processes and generalized Pólya urns , Stochastic Process. Appl., 110
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H. Renlund: Nonconvergence to strictly unstable boundary points in stochastic approximation . Preprint (2009), 9 pages
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