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Handbook Of Neuroevolution Through Erlang Gene I Sher

  • SKU: BELL-4158198
Handbook Of Neuroevolution Through Erlang Gene I Sher
$ 31.00 $ 45.00 (-31%)

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Handbook Of Neuroevolution Through Erlang Gene I Sher instant download after payment.

Publisher: Springer
File Extension: PDF
File size: 8.49 MB
Pages: 789
Author: Gene I Sher
ISBN: 9781461444633, 1461444632
Language: English
Year: 2013

Product desciption

Handbook Of Neuroevolution Through Erlang Gene I Sher by Gene I Sher 9781461444633, 1461444632 instant download after payment.

Handbook of Neuroevolution Through Erlang presents both the theory behind, and the methodology of, developing a neuroevolutionary-based computational intelligence system using Erlang. With a foreword written by Joe Armstrong, this handbook offers an extensive tutorial for creating a state of the art Topology and Weight Evolving Artificial Neural Network (TWEANN) platform. In a step-by-step format, the reader is guided from a single simulated neuron to a complete system. By following these steps, the reader will be able to use novel technology to build a TWEANN system, which can be applied to Artificial Life simulation, and Forex trading. Because of Erlang's architecture, it perfectly matches that of evolutionary and neurocomptational systems. As a programming language, it is a concurrent, message passing paradigm which allows the developers to make full use of the multi-core & multi-cpu systems. Handbook of Neuroevolution Through Erlang explains how to leverage Erlang's features in the field of machine learning, and the system's real world applications, ranging from algorithmic financial trading to artificial life and robotics. Read more... Part 1. FOUNDATIONS -- Introduction to Neural Networks -- Introduction to Evolutionary Computation -- Introduction to Neuroevolutionary Methods -- The Unintentional Neural Network Programming Language -- Introduction: Applications & Motivations -- Part 2. NEUROEVOLUTION: TAKING THE FIRST STEP -- Developing a Feed Forward Neural Network -- Adding the "Stochastic Hill-Climber" Learning Algorithm -- Developing a Simple Neuroevolutionary Platform -- Testing the Neuroevolutionary System -- Part 3. A Case Study -- DXNN: A Case Study -- Part 4. Advanced Neuroevolution: Creating the Cutting Edge -- 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 -- Part 5. Applications -- Artificial Life -- Evolving Currency Trading Agents -- Part 6. Promises Kept -- Conclusion

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