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020 _a9781461444633
_9978-1-4614-4463-3
024 7 _a10.1007/978-1-4614-4463-3
_2doi
035 _ato000483619
040 _aSpringer
_cSpringer
_dRU-ToGU
050 4 _aQA76.758
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_2bicssc
072 7 _aUL
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072 7 _aCOM051230
_2bisacsh
082 0 4 _a005.1
_223
100 1 _aSher, Gene I.
_eauthor.
_9413961
245 1 0 _aHandbook of Neuroevolution Through Erlang
_helectronic resource
_cby Gene I. Sher.
260 _aNew York, NY :
_bSpringer New York :
_bImprint: Springer,
_c2013.
300 _aXX, 831 p. 172 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
505 0 _aIntroduction: 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.
520 _aHandbook 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.
650 0 _aComputer Science.
_9155490
650 0 _aSoftware engineering.
_9566225
650 0 _aArtificial intelligence.
_9274099
650 0 _aBioinformatics.
_9303853
650 1 4 _aComputer Science.
_9155490
650 2 4 _aSoftware Engineering/Programming and Operating Systems.
_9303115
650 2 4 _aArtificial Intelligence (incl. Robotics).
_9274102
650 2 4 _aComputational Biology/Bioinformatics.
_9306755
710 2 _aSpringerLink (Online service)
_9143950
773 0 _tSpringer eBooks
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4614-4463-3
912 _aZDB-2-SCS
999 _c356441