Computational Techniques for Modelling Learning in Economicsby Thomas Brenner
Comp. Techniques for Modelling Learning Economics offers a critical overview on the computational techniques that are frequently used for modelling learning in economics. It is a collection of papers, each of which focuses on a different way of modelling learning, including the techniques of evolutionary algorithms, genetic programming, neural networks, classifier systems, local interaction models, least squares learning, Bayesian learning, boundedly rational models and cognitive learning models. The work even includes new innovative ways of modelling learning that are not common in the literature, like the study of the decomposition of task or the modelling of cognitive learning.
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