I. Introduction.- 1. Introduction.- 2. The Core Topics; Learning and Computational Economics.- 2.1 Learning.- 2.1.1 A Definition.- 2.1.2 The Necessity of Learning in Economic Models.- 2.1.3 Methods of Describing Economic Learning.- 2.2 Computational Economics.- 2.2.1 Names and Definitions.- 2.2.2 The Role of Computational Economics in Economic Research.- 2.2.3 Agent Based Economics.- 2.2.4 Artificial Economic Agents.- 2.2.5 Differences to Analytical Models.- 2.3 Summary.- 3. An Exemplary Introduction to Structure and Application of Genetic Algorithms in Economic Research.- 3.1 Introduction.- 3.2 The Economic Problem: A Model of Regional Monopolies.- 3.2.1 The General Structure of the Model.- 3.2.2 The Consequences of Bounded Rationality.- 3.3 The Genetic Algorithm.- 3.3.1 Introduction.- 3.3.2 Problem Definition.- 3.3.3 Execution of the Algorithm.- 3.4 A Simple Example.- 3.4.1 Coding and Running the GA.- 3.4.2 Representation of the Results.- 3.4.3 Interpretation.- 3.5 Summary.- II. General Analysis of Genetic Algorithms.- 4. Methods for the General Analysis of Genetic Algorithms as Economic Learning Techniques.- 4.1 Introduction.- 4.1.1 The Schema Theorem.- 4.1.2 Concepts from Population Genetics.- 4.2 Genetic Algorithm Learning as a Markov Process.- 4.2.1 The Basics.- 4.2.2 Markov Chain Analysis.- 4.3 Genetic Algorithm Learning as an Evolutionary Process.- 4.3.1 Populations as Near Nash Equilibria.- 4.3.2 Evolutionary Stability of Genetic Populations.- 4.3.3 Evolutionary Dynamics.- 4.4 Genetic Algorithms as Learning Processes.- 4.4.1 Learning by Imitation.- 4.4.2 Learning by Communication.- 4.4.3 Learning by Experiment.- 4.4.4 GA Learning as a Compound Learning Mechanism.- 4.5 Summary.- 5. Statistical Aspects of the Analysis of Economic Genetic Algorithms.- 5.1 Introduction.- 5.2 Analysis.- 5.3 Summary.- III. Economic Applications and Technical Variations.- 6. Modifications: Election and Meta!Learning.- 6.1 Introduction.- 6.2 Election.- 6.3 Meta Learning.- 6.4 Comparison of Learning Techniques.- 6.5 Summary.- Appendix: Technical Characteristics of the Meta Learning Process.- 7. Extensions: Variable Time Horizon of Selection.- 7.1 Introduction.- 7.2 The Economic Problem: A Cobweb Model with Declining Average Production Costs.- 7.2.1 The General Structure of the Model.- 7.2.2 Theoretical Results.- 7.3 The Genetic Algorithm.- 7.4 Simulation Results.- 7.4.1 Heterogeneities.- 7.4.2 Cycles.- 7.5 Summary.- 8. Algorithms with Real Valued Coding.- 8.1 Introduction.- 8.2 The Economic Model: Consumer Choice.- 8.2.1 The General Structure of the Model.- 8.2.2 The Basic Model.- 8.2.3 The Enhanced Model.- 8.3 The Genetic Algorithm.- 8.3.1 The Basics.- 8.3.2 Coding.- 8.3.3 Standard Operators.- 8.3.4 Enhanced Operators.- 8.3.5 Coping with the Constraints.- 8.4 Simulations and Results.- 8.4.1 Fixed Prices.- 8.4.2 Flexible Prices, High Elasticity.- 8.4.3 Flexible Prices, Low Elasticity.- 8.4.4 Summary of Results.- 8.5 Conclusions.- 8.5.1 The Influence of State Dependency.- 8.5.2 The Influence of Different Learning Schemes.- 8.6 Summary.- Appendix: Statistical Results.- 9. A Multi Population Algorithm.- 9.1 Introduction.- 9.2 The Economic Model: A Basic Overlapping Generations Model with Money.- 9.2.1 The General Structure of the Model.- 9.2.2 Theoretical Results.- 9.3 The Genetic Algorithm.- 9.4 Simulations and Results.- 9.4.1 The Election GA.- 9.4.2 Meta Mutation.- 9.5 An Overlapping Generations Model with Heterogeneous Agents.- 9.5.1 The Extensions to the Basic Model.- 9.5.2 The Role of Bounded Rationality.- 9.5.3 The Credit Market.- 9.5.4 The Money Market.- 9.5.5 The Proceeding of the Model.- 9.5.6 A Walrasian Credit Market.- 9.5.7 Theoretical Conclusions: Stability Properties of the Expec-tations Equilibrium Revisited.- 9.5.8 The Genetic Algorithm.- 9.5.9 Results.- 9.6 Summary.- 10. Final Remarks.