Computational Techniques for Modelling Learning in Economics / Edition 1

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Overview

Computational Techniques for Modelling Learning in 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. 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 guiding in the field of modelling learning in computation economics.
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Product Details

  • ISBN-13: 9780792385035
  • Publisher: Springer US
  • Publication date: 5/31/1999
  • Series: Advances in Computational Economics Series , #11
  • Edition description: 1999
  • Edition number: 1
  • Pages: 391
  • Product dimensions: 9.21 (w) x 6.14 (h) x 0.94 (d)

Table of Contents

Preface
List of Contributors
Pt. 1 Simulating in Economics
Evolutionary Economics and Simulation 3
Simulation as a Tool to Model Stochastic Processes in Complex Systems 45
Pt. 2 Evolutionary Approaches
Learning by Genetic Algorithms in Economics? 73
Can Learning-Agent Simulations Be Used for Computer Assisted Design in Economics? 101
On the Emergence of Attitudes towards Risk 123
Interdependencies, Nearly-decomposability and Adaptation 145
Pt. 3 Neural Networks and Local Interaction
Neural Networks in Economics 169
Genetic Algorithms and Neural Networks: A Comparison Based on the Repeated Prisoners Dilemma 197
Local Interaction as a Model of Social Interaction? 221
Pt. 4 Boundedly Rational and Rational Models
Memory, Learning and the Selection of Equilibria in a Model with Non-Uniqueness 243
A Behavioral Approach to a Strategic Market Game 261
Bayesian Learning in Optimal Growth Models under Uncertainty 283
Pt. 5 Cognitive Learning Models
Modelling Bounded Rationality in Agent-based Simulations Using the Evolution of Mental Models 305
Cognitive Learning in Prisoner's Dilemma Situations 333
A Cognitively Rich Methodology for Modelling Emergent Socioeconomic Phenomena 363
Index 387
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