Overview
- Introduces the paradigm of self-evolvability enabling the reader to combine technological, socioeconomical, and scientific aspects of complexity into one concentrated expression
- Emphasizing the multiple features involved by self-evolvability, with a focus on innovative concepts and models
- Includes various case studies representing a source of inspiration for emerging methods, technologies and systems in their needed transition from adaptable and evolvable towards self-evolvable
Part of the book series: Understanding Complex Systems (UCS)
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Table of contents (12 chapters)
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Front Matter
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Back Matter
Keywords
About this book
This monograph presents key method to successfully manage the growing complexity of systems  where conventional engineering and scientific methodologies and technologies based on learning and adaptability come to their limits and new ways are nowadays required. The transition from adaptable to evolvable and finally to self-evolvable systems is highlighted, self-properties such as self-organization, self-configuration, and self-repairing are introduced and challenges and limitations of the self-evolvable engineering systems are evaluated.
Authors and Affiliations
Bibliographic Information
Book Title: Self-Evolvable Systems
Book Subtitle: Machine Learning in Social Media
Authors: Octavian Iordache
Series Title: Understanding Complex Systems
DOI: https://doi.org/10.1007/978-3-642-28882-1
Publisher: Springer Berlin, Heidelberg
eBook Packages: Physics and Astronomy, Physics and Astronomy (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2012
Hardcover ISBN: 978-3-642-28881-4Published: 05 July 2012
Softcover ISBN: 978-3-642-43149-4Published: 09 August 2014
eBook ISBN: 978-3-642-28882-1Published: 05 July 2012
Series ISSN: 1860-0832
Series E-ISSN: 1860-0840
Edition Number: 1
Number of Pages: XXII, 278
Topics: Complexity, Computational Intelligence, Applications of Nonlinear Dynamics and Chaos Theory