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Handbook of Neuroevolution Through Erlang presents both the theory behind, and the methodology of, developing a neuroevolutionary-based computational intelligence system using Erlang.
Introduction: Applications & Motivations.- Introduction to Neural Networks.- Introduction to Evolutionary Computation.- Introduction to Neuroevolutionary Methods.- The Unintentional Neural Network Programming Language.- Developing a Feed Forward Neural Network.- Adding the “Stochastic Hill-Climber” Learning Algorithm.- Developing a Simple Neuroevolutionary Platform.- Testing the Neuroevolutionary System.- DXNN: A Case Study.- Decoupling & Modularizing Our Neuroevolutionary Platform.- Keeping Track of Important Population and Evolutionary Stats.- The Benchmarker.- Creating the Two Slightly More Complex Benchmarks.- Neural Plasticity.- Substrate Encoding.- Substrate Plasticity.- Artificial Life.- Evolving Currency Trading Agents.- Conclusion.