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Handbook of Neuroevolution Through Erlang

  • Book
  • © 2013

Overview

Authors:
  1. Gene I. Sher

    1. University of Central Florida, Orlando, USA

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  • Provides a friendly step-by-step guide on the construction of Topology and Weight Evolving Artificial Neural Network systems from start to finish

  • Covers novel material for using Erlang in the construction of TWEANN systems

  • Explains why Neural Network based Computational Intelligence systems map perfectly to Erlang’s architecture, and the importance of this programming language to the future of computational intelligence

  • Introduces new TWEANN algorithms, with the final result being a concurrent, cutting edge, direct and indirect encoded, plasticity enabled, TWEANN platform

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Table of contents (20 chapters)

  1. Front Matter

    Pages i-xx
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  2. Introduction: Applications & Motivations

    • Gene I. Sher
    Pages 1-39

  3. Foundations

    1. Front Matter

      Pages 41-41
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    2. Introduction to Neural Networks

      • Gene I. Sher
      Pages 43-79

    3. Introduction to Evolutionary Computation

      • Gene I. Sher
      Pages 81-104

    4. Introduction to Neuroevolutionary Methods

      • Gene I. Sher
      Pages 105-141

    5. The Unintentional Neural Network Programming Language

      • Gene I. Sher
      Pages 143-150

  4. Neuroevolution: Taking the First Step

    1. Front Matter

      Pages 151-151
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    2. Developing a Feed Forward Neural Network

      • Gene I. Sher
      Pages 153-185

    3. Adding the “Stochastic Hill-Climber” Learning Algorithm

      • Gene I. Sher
      Pages 187-227

    4. Developing a Simple Neuroevolutionary Platform

      • Gene I. Sher
      Pages 229-346

    5. Testing the Neuroevolutionary System

      • Gene I. Sher
      Pages 347-395

  5. A Case Study

    1. Front Matter

      Pages 397-397
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    2. DXNN: A Case Study

      • Gene I. Sher
      Pages 399-444

  6. Advanced Neuroevolution: Creating the Cutting Edge

    1. Front Matter

      Pages 445-445
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    2. Decoupling & Modularizing Our Neuroevolutionary Platform

      • Gene I. Sher
      Pages 447-526

    3. Keeping Track of Important Population and Evolutionary Stats

      • Gene I. Sher
      Pages 527-545

    4. The Benchmarker

      • Gene I. Sher
      Pages 547-571

    5. Creating the Two Slightly More Complex Benchmarks

      • Gene I. Sher
      Pages 573-608

    6. Neural Plasticity

      • Gene I. Sher
      Pages 609-659
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Keywords

About this book

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.

Authors and Affiliations

  • University of Central Florida, Orlando, USA

    Gene I. Sher

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