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Handbook of Neuroevolution Through Erlang [electronic resource] / by Gene I. Sher

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Creatore: Sher, Gene I. Visualizza persona
Titolo: Handbook of Neuroevolution Through Erlang [electronic resource] / by Gene I. Sher
Link to work: Handbook of neuroevolution through Erlang Visualizza cluster
Pubblicazione: New York, NY : Springer New York : Imprint : Springer, 2013
Estensione: XX, 831 p. 172 illus. digital.
Disciplina: 005.1
Classificazione LOC: QA76.758
Accesso ente: SpringerLink (Online service)
Nota di contenuto: <p>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. </p>.
Restrizioni accesso: Access restricted by licensing agreement.
Sommario/riassunto: <i>Handbook of Neuroevolution Through Erlang</i> 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. <i>Handbook of Neuroevolution Through Erlang</i> 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.
Opere correlate: Springer ebooks
ISBN: 9781461444633
Formato: Risorse elettroniche
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 11153396
Localizzazioni e accesso elettronico
Lo trovi qui: Yale University
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Altra ed. diverso supporto: Printed edition: 9781461444626