-of-thumb?approximation to optimal behavior by trial-and-error methods as Friedman (1953) proposed long ago We find that such individual learning …

certain features of monetary policy rules that facilitate learning. However a treatment of policy design for learnability in … worlds where agents have potentially misspecified their learning models has yet to surface. This paper provides such a … understanding of the workings of the economy and that their learning the reduced forms of the economy is subject to potentially …

This paper examines the learning dynamics of boundedly rational agents, who are asked to voluntarily contribute to a … striking differences between strategies played in the two games are confirmed by simulations, where the learning process is …

Today, intelligent systems that offer artificial intelligence capabilities often rely on machine learning. Machine … learning describes the capacity of systems to learn from problem-specific training data to automate the process of analytical … model building and solve associated tasks. Deep learning is a machine learning concept based on artificial neural networks …

optimise under limited-information model-consistent learning, where each agent knows the parameters related to his …/her optimization problem. Under this learning approach the effect of a monetary policy shock on output and inflation is more muted but … learning version, we .find stronger expansionary effects of an increase in government expenditure during periods of downturns …

in learning the material have been determined. Besides its uses, 3 limitations of this tool have also been found … one respondent). Homework – making a summarized mind map for a particular chapter, was helpful for learning the material …

learning process of purely and impurely altruistic agents and find that in both cases the contribution level converges towards … corresponds to findings from experiments on voluntary contribution to a public good. Crucial determinants of the learning process …