Description: Computational Techniques for Modelling Learning in Economics, Hardcover by Brenner, Thomas (EDT), ISBN 0792385039, ISBN-13 9780792385035, Like New Used, Free shipping in the US Computational Techniques for Modelling Learning in Economics offers a critical overview of 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. Each paper describes the technique it uses, gives an example of its applications, and discusses the advantages and disadvantages of the technique. Hence, th offers some guidance in the field of modelling learning in computation economics. In addition, the material contains state-of-the-art applications of the learning models in economic contexts such as the learning of preference, the study of bidding behaviour, the development of expectations, the analysis of economic growth, the learning in the repeated prisoner's dilemma, and the changes of cognitive models during economic transition. The work even includes innovative ways of modelling learning that are not common in the literature, for example the study of the decomposition of task or the modelling of cognitive learning.
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Book Title: Computational Techniques for Modelling Learning in Economics
Number of Pages: Xiii, 391 Pages
Language: English
Publication Name: Computational Techniques for Modelling Learning in Economics
Publisher: Springer
Subject: Economics / General, Econometrics
Publication Year: 1999
Item Weight: 58.2 Oz
Type: Textbook
Author: Thomas Brenner
Item Length: 9.3 in
Subject Area: Business & Economics
Series: Advances in Computational Economics Ser.
Item Width: 6.1 in
Format: Hardcover
