Abstract
In the context of learning in games, belief learning refers to models in which players are engaged in a dynamic game and each player optimizes with respect to a prediction rule that gives a forecast of next-period opponent behaviour as a function of the current history. This article focuses on the most studied class of dynamic games, namely, two-player discounted repeated games with finite stage game action sets and perfect monitoring.
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Nachbar, J. (2018). Learning and Evolution in Games: Belief Learning. In: The New Palgrave Dictionary of Economics. Palgrave Macmillan, London. https://doi.org/10.1057/978-1-349-95189-5_2645
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DOI: https://doi.org/10.1057/978-1-349-95189-5_2645
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