Handbook of Neuroevolution Through Erlang

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Sprache: Englisch

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Beschreibung

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.

Zusammenfassung

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

Inhaltsverzeichnis

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.

Details

Erscheinungsjahr:	2016
Genre:	Informatik
Rubrik:	Naturwissenschaften & Technik
Medium:	Taschenbuch
Seiten:	852
Inhalt:	xx 831 S. 172 s/w Illustr. 1 s/w Tab. 831 p. 172 illus.
ISBN-13:	9781493945887
ISBN-10:	1493945882
Sprache:	Englisch
Ausstattung / Beilage:	Paperback
Einband:	Kartoniert / Broschiert
Autor:	Sher, Gene I.
Auflage:	Softcover reprint of the original 1st ed. 2013
Hersteller:	Springer New York Springer US, New York, N.Y.
Maße:	235 x 155 x 46 mm
Von/Mit:	Gene I. Sher
Erscheinungsdatum:	23.08.2016
Gewicht:	1,264 kg