This report introduces a novel approach to performing inference and learning in Dynamic Bayesian Networks (DBN). The … traditional approach to inference and learning in DBNs involves conditioning on one or more finite-length observation sequences … solving inference problems (i.e., computing P(X|Φ)) and learning problems (i.e., computing P(Θ|Φ)) using techniques from the …

decision making is coming to an understanding, and learning how to act. A set of behavioral implications (such as … experimentation, habits, imitation, empathy, etc..) follows as patterns of learning in different contexts. Further, conventions emerge … as a means of stabilizing mutual expectations. Stability of conventions on the one hand and learning over time on the …

This chapter provides a survey of the recent work on learning in the context of macroeconomics. Learning has several … roles. First, it provides a boundedly rational model of how rational expectations can be achieved. Secondly, learning acts … as a selection device in models with multiple REE (rational expectations equilibria). Third, the learning dynamics …