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121116s2013 xxu| s |||| 0|eng d
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9781461444633
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978-1-4614-4463-3
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10.1007/978-1-4614-4463-3
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doi
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(DE-He213)978-1-4614-4463-3
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11153396
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QA76.758
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Sher, Gene I.
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Handbook of Neuroevolution Through Erlang
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[electronic resource] /
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by Gene I. Sher.
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New York, NY :
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Springer New York :
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Imprint: Springer,
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2013.
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XX, 831 p. 172 illus.
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digital.
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<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>.
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Access restricted by licensing agreement.
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<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.
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Access is available to the Yale community.
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Computer science.
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Software engineering.
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Artificial intelligence.
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Bioinformatics.
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SpringerLink (Online service)
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Springer ebooks.
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8
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Printed edition:
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9781461444626
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0
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Online Resource
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Online book
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https://yale.idm.oclc.org/login?URL=http://dx.doi.org/10.1007/978-1-4614-4463-3
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QA76.758
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Yale Internet Resource
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Yale Internet Resource >> None|DELIM|11317425
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online resource
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2012-12-03T10:11:01.000Z
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DO NOT EDIT. DO NOT EXPORT.
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http://dx.doi.org/10.1007/978-1-4614-4463-3