Handbook of Neuroevolution Through Erlang

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...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Sher, Gene I. (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: New York, NY : Springer New York : Imprint: Springer, 2013.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
LEADER 03493nam a22004695i 4500
001 978-1-4614-4463-3
003 DE-He213
005 20130727034746.0
007 cr nn 008mamaa
008 121116s2013 xxu| s |||| 0|eng d
020 |a 9781461444633  |9 978-1-4614-4463-3 
024 7 |a 10.1007/978-1-4614-4463-3  |2 doi 
040 |d GrThAP 
050 4 |a QA76.758 
072 7 |a UMZ  |2 bicssc 
072 7 |a UL  |2 bicssc 
072 7 |a COM051230  |2 bisacsh 
082 0 4 |a 005.1  |2 23 
100 1 |a Sher, Gene I.  |e author. 
245 1 0 |a Handbook of Neuroevolution Through Erlang  |h [electronic resource] /  |c by Gene I. Sher. 
264 1 |a New York, NY :  |b Springer New York :  |b Imprint: Springer,  |c 2013. 
300 |a XX, 831 p. 172 illus.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
505 0 |a 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. 
520 |a 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. 
650 0 |a Computer science. 
650 0 |a Software engineering. 
650 0 |a Artificial intelligence. 
650 0 |a Bioinformatics. 
650 1 4 |a Computer Science. 
650 2 4 |a Software Engineering/Programming and Operating Systems. 
650 2 4 |a Artificial Intelligence (incl. Robotics). 
650 2 4 |a Computational Biology/Bioinformatics. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9781461444626 
856 4 0 |u http://dx.doi.org/10.1007/978-1-4614-4463-3  |z Full Text via HEAL-Link 
912 |a ZDB-2-SCS 
950 |a Computer Science (Springer-11645)