TY  - BOOK
AU  - 
ED  - SpringerLink (Online service)
TI  - Self-Evolvable Systems: Machine Learning in Social Media 
T2  - Understanding Complex Systems,
SN  - 9783642288821
AV  - QA76.9.M35 
U1  - 620 23
PY  - 2012///
CY  - Berlin, Heidelberg
PB  - Springer Berlin Heidelberg, Imprint: Springer
KW  - Engineering
KW  - Physics
KW  - Complexity
KW  - Computational Intelligence
KW  - Nonlinear Dynamics
N1  - 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; ZDB-2-PHA
N2  - 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
UR  - http://dx.doi.org/10.1007/978-3-642-28882-1
ER  -