+612 9045 4394
 
CHECKOUT
Computational Techniques for Modeling Learning in Economics : Advances in Computational Economics - Thomas Brenner

Computational Techniques for Modeling Learning in Economics

Advances in Computational Economics

By: Thomas Brenner (Editor)

Hardcover

Published: December 2009
Ships: 7 to 10 business days
7 to 10 business days
RRP $745.99
$516.35
31%
OFF
or 4 easy payments of $129.09 with Learn more

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, the book 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.

Preface
List of Contributors
Simulating in Economics
Evolutionary Economics and Simulationp. 3
Simulation as a Tool to Model Stochastic Processes in Complex Systemsp. 45
Evolutionary Approaches
Learning by Genetic Algorithms in Economics?p. 73
Can Learning-Agent Simulations Be Used for Computer Assisted Design in Economics?p. 101
On the Emergence of Attitudes towards Riskp. 123
Interdependencies, Nearly-decomposability and Adaptationp. 145
Neural Networks and Local Interaction
Neural Networks in Economicsp. 169
Genetic Algorithms and Neural Networks: A Comparison Based on the Repeated Prisoners Dilemmap. 197
Local Interaction as a Model of Social Interaction?p. 221
Boundedly Rational and Rational Models
Memory, Learning and the Selection of Equilibria in a Model with Non-Uniquenessp. 243
A Behavioral Approach to a Strategic Market Gamep. 261
Bayesian Learning in Optimal Growth Models under Uncertaintyp. 283
Cognitive Learning Models
Modelling Bounded Rationality in Agent-based Simulations Using the Evolution of Mental Modelsp. 305
Cognitive Learning in Prisoner's Dilemma Situationsp. 333
A Cognitively Rich Methodology for Modelling Emergent Socioeconomic Phenomenap. 363
Indexp. 387
Table of Contents provided by Blackwell. All Rights Reserved.

ISBN: 9780792385035
ISBN-10: 0792385039
Series: Advances in Computational Economics
Audience: Professional
Format: Hardcover
Language: English
Number Of Pages: 391
Published: December 2009
Publisher: Springer
Country of Publication: NL
Dimensions (cm): 23.5 x 15.5  x 2.54
Weight (kg): 1.65