ISBN:3790813842
TITLE: Learning in Economics
AUTHOR: T. Riechmann
TOC:

Part 1. Introduction
1 Introduction 3
2. The Core Topics: Learning and Computational Economics 7
2.1 Learning 7
2.1.1 A Definition 7
2.1.2 The Necessity of Learning in Economic Models 8
2.1.3 Methods of Describing Economic Learning 10
2.2 Computational Economics 11
2.2.1 Names and Definitions 12
2.2.2 The Role of Computational Economics in Economic Research 12
2.2.3 Agent Based Economics 13
2.2.4 Artificial Economic Agents 14
2.2.5 Differences to Analytical Models 16
2.3 Summary 18
3. An Exemplary Introduction to Structure and Application of Genetic Algorithms in Economic Research 19
3.1 Introduction 19
3.2 The Economic Problem: A Model of Regional Monopolies 19
3.2.1 The General Structure of the Model 19
3.2.2 The Consequences of Bounded Rationality 21
3.3 The Genetic Algorithm 21
3.3.1 Introduction 21
3.3.2 Problem Definition 22
3.3.3 Execution of the Algorithm 24
3.4 A Simple Example 28
3.4.1 Coding and Running the GA 28
3.4.2 Representation of the Results 33
3.4.3 Interpretation 34
3.5 Summary 35
Part II. General Analysis of Genetic Algorithms
4. Methods for the General Analysis of Genetic Algorithms as Economic
Learning Techniques 39
4.1 Introduction 39
4.1.1 The Schema Theorem 40
4.1.2 Concepts from Population Genetics 41
4.2 Genetic Algorithm Learning as a Markov Process 41
4.2.1 The Basics 41
4.2.2 Markov Chain Analysis 43
4.3 Genetic Algorithm Leaming as an Evolutionary Process 49
4.3.1 Populations as Near Nash Equilibria 51
4.3.2 Evolutionary Stability of Genetic Populations 51
4.3.3 Evolutionary Dynamics 54
4.4 Genetic Algorithms as Learning Processes 56
4.4.1 Learning by Imitation 57
4.4.2 Learning by Communication 59
4.4.3 Learning by Experiment 60
4.4.4 GA Learning as a Compound Learning Mechanism 61
4.5 Summary 61
5. Statistical Aspects of the Analysis of Economic Genetic Algorithms 63
5.1 Introduction 63
5.2 Analysis 64
5.3 Summary 68
Part III. Economic Applications and Technical Variations
6. Modifications: Election and Meta-Learning 73
6.1 Introduction 73
6.2 Election 74
6.3 Meta Learning 79
6.4 Comparison of Learning Techniques 90
6.5 Summary 94
Appendix: Technical Characteristics of the Meta Learning Process 96
7. Extensions: Variable Time Horizon of Selection 97
7.1 Introduction 97
7.2 The Economic Problem: A Cobweb Model with Declining Average Production Costs 97
7.2.1 The General Structure of the Model 97
7.2.2 Theoretical Results 99
7.3 The Genetic Algorithm 100
7.4 Simulation Results 102
7.4.1 Heterogeneities 103
7.4.2 Cycles 105
7.5 Summary 112
8. Algorithms with Real Valued Coding 115
8.1 Introduction 115
8.2 The Economic Model: Consumer Choice 115
8.2.1 The General Structure of the Model 115
8.2.2 The Basic Model 116
8.2.3 The Enhanced Model 117
8.3 The Genetic Algorithm 118
8.3.1 The Basics 118
8.3.2 Coding 118
8.3.3 Standard Operators 119
8.3.4 Enhanced Operators 120
8.3.5 Coping with the Constraints 121
8.4 Simulations and Results 122
8.4.1 Fixed Prices 123
8.4.2 Flexible Prices, High Elasticity 124
8.4.3 Flexible Prices, Low Elasticity 125
8.4.4 Summary of Results 126
8.5 Conclusions 128
8.5.1 The Influence of State Dependency 128
8.5.2 The Influence of Different Learning Schemes 132
8.6 Summary 133
Appendix: Statistical Results 135
9. A Multi Population Algorithm 137
9.1 Introduction 137
9.2 The Economic Model: A Basic Overlapping Generations Model
with Money 138
9.2.1 The General Structure of the Model 138
9.2.2 Theoretical Results 138
9.3 The Genetic Algorithm 142
9.4 Simulations and Results 144
9.4.1 The Election GA 144
9.4.2 Meta Mutation 145
9.5 An Overlapping Generations Model with Heterogeneous Agents 147
9.5.1 The Extensions to the Basic Model 148
9.5.2 The Role of Bounded Rationality 149
9.5.3 The Credit Market 150
9.5.4 The Money Market 153
9.5.5 The Proceeding of the Model 155
9.5.6 A Walrasian Credit Market 156
9.5.7 Theoretical Conclusions: Stability Properties of the Expectations
Equilibrium Revisited 161
9.5.8 The Genetic Algorithm 162
9.5.9 Results 164
9.6 Summary 165
10. Final Remarks 167 
Bibliography 169
Index 177
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