• ВХОД

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    Полное описание

    Cartesian Genetic Programming : сборник / edited by Julian F. Miller. ; editor. J. Miller. - Berlin ; Heidelberg : Springer, 2011. - on-line. - (Natural Computing Series). - URL: http://dx.doi.org/10.1007/978-3-642-17310-3. - Загл. с экрана. - ISBN 978-3-642-17310-3. - Текст : электронный.
    Содержание:
    Introduction -- Cartesian Genetic Programming -- Modular Cartesian Genetic Programming -- Self-modifying Cartesian Genetic Programming -- Evolution of Electronic Circuits -- Image Processing -- Developmental Approaches -- Artificial Neural Approaches -- Medical Applications -- Hardware Acceleration -- Control Applications -- Evolutionary Art -- Future Directions -- App. A, A Bibliography of CGP Papers -- App. B, CGP Software.

    ГРНТИ УДК
    50.05.13004.42

    Рубрики:
    computer science
    computers
    artificial intelligence
    application software
    computer-aided engineering
    electrical engineering
    computer Science
    theory of Computation
    electrical Engineering
    artificial Intelligence (incl Robotics)
    computer-Aided Engineering (CAD, CAE) and Design
    computer Appl in Arts and Humanities

    Аннотация: Cartesian Genetic Programming (CGP) is a highly effective and increasingly popular form of genetic programming. It represents programs in the form of directed graphs, and a particular characteristic is that it has a highly redundant genotype–phenotype mapping, in that genes can be noncoding. It has spawned a number of new forms, each improving on the efficiency, among them modular, or embedded, CGP, and self-modifying CGP. It has been applied to many problems in both computer science and applied sciences.   This book contains chapters written by the leading figures in the development and application of CGP, and it will be essential reading for researchers in genetic programming and for engineers and scientists solving applications using these techniques. It will also be useful for advanced undergraduates and postgraduates seeking to understand and utilize a highly efficient form of genetic programming.  .
    Доп. точки доступа:
    Miller, J.\editor.\

    http://dx.doi.org/10.1007/978-3-642-17310-3


    Держатели документа:
    Государственная публичная научно-техническая библиотека России : 123298, г. Москва, ул. 3-я Хорошевская, д. 17 (Шифр в БД-источнике (KATBW): -941766974)

    Шифр в сводном ЭК: b021e7e111e1dd1db9f96a1743036062



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