Self-Evolvable Systems Machine Learning in Social Media
Titre:
Self-Evolvable Systems Machine Learning in Social Media
ISBN (Numéro international normalisé des livres):
9783642288821
Auteur personnel:
Edition:
1st ed. 2012.
PRODUCTION_INFO:
Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2012.
Description physique:
XXII, 278 p. online resource.
Collections:
Understanding Complex Systems,
Table des matières:
Introduction -- General Framework -- Differential Models -- Informational Criteria -- Self-Evolvability for Physical and Chemical Systems -- Self-Evolvability for Biosystems -- Self-Evolvability for Cognitive Systems -- Control Systems -- Manufacturing Systems -- Concept Lattices -- Design of Experiments -- Perspectives.
Extrait:
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.
Auteur collectif ajouté:
Accès électronique:
Full Text Available From Springer Nature Physics and Astronomy 2012 Packages
Langue:
Anglais