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Thomas . Ed(S): Brenner - Computational Techniques for Modelling Learning in Economics - 9780792385035 - V9780792385035
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Computational Techniques for Modelling Learning in Economics

€ 247.03
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Description for Computational Techniques for Modelling Learning in Economics Hardback. 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. Editor(s): Brenner, Thomas. Series: Advances in Computational Economics. Num Pages: 391 pages, biography. BIC Classification: KC; PBW. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 234 x 156 x 23. Weight in Grams: 1650.
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. ... Read more

Product Details

Format
Hardback
Publication date
1999
Publisher
Kluwer Academic Publishers United States
Number of pages
391
Condition
New
Series
Advances in Computational Economics
Number of Pages
391
Place of Publication
Dordrecht, Netherlands
ISBN
9780792385035
SKU
V9780792385035
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15

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