03373nam^a22003855i^450001214135020121116200700.0m^^^^^^^^^^^^^^^^^cr^nn^008mamaa121116s2013^^^^xxu|^^^^o^^^^||||^0|eng^d978146144463310.1007/978-1-4614-4463-3doi(Springer)spr 978-1-4614-4463-3QA76.758005.123Sher, Gene I.http://share-vde.org/sharevde/rdfBibframe/Agent/4099872http://viaf.org/viaf/296443788Handbook of Neuroevolution Through Erlang[electronic resource] /by Gene I. Sher.New York, NY :Springer New York :Imprint: Springer,2013.XX, 831 p. 172 illus.digital.<p>Introduction: Applications &amp; 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 &amp; 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>.<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 &amp; 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.Computer science.http://id.loc.gov/authorities/subjects/sh89003285Software engineering.http://id.loc.gov/authorities/subjects/sh87007398Artificial intelligence.http://id.loc.gov/authorities/subjects/sh85008180Bioinformatics.http://id.loc.gov/authorities/subjects/sh00003585Computer science.http://id.loc.gov/authorities/subjects/sh89003285Software Engineering/Programming and Operating Systems.Artificial Intelligence (incl. Robotics)Computational Biology/Bioinformatics.SpringerLink (Online service)http://viaf.org/viaf/148105729Printed edition:9781461444626Access to the SpringerLink online version restricted; authentication may be required:http://dx.doi.org/10.1007/978-1-4614-4463-3incoming 001978-1-4614-4463-3incoming 003DE-He213springer_12jHandbook of neuroevolution through Erlanghttp://share-vde.org/sharevde/rdfBibframe/Work/3471482-1MARSUMICHspringer-dld ERLoad20121203