Digitally Evolving Models for Dynamically Adaptive Systems

Developing a Dynamically Adaptive System (DAS) requires a developer to identify viable target systems that can be adopted by the DAS at runtime in response to specific environmental conditions, while satisfying critical properties. This paper describes a preliminary investigation into using digital...

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Veröffentlicht in:	International Workshop on Software Engineering for Adaptive and Self-Managing Systems (SEAMS '07) S. 13
Hauptverfasser:	Goldsby, Heather J., Knoester, David B., Cheng, Betty H. C., McKinley, Philip K., Ofria, Charles A.
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	Washington, DC, USA IEEE Computer Society 20.05.2007 IEEE
Schriftenreihe:	ACM Conferences
Schlagworte:	Adaptive systems Computer aided instruction Computer science Computing methodologies > Machine learning > Machine learning approaches > Neural networks Condition monitoring Evolution (biology) Genetic mutations Hardware > Emerging technologies > Circuit substrates > Cellular neural networks Organisms Runtime environment Software and its engineering > Software creation and management > Software post-development issues > Software reverse engineering Software and its engineering > Software organization and properties > Software system structures > Software architectures Space exploration Theory of computation > Theory and algorithms for application domains > Machine learning theory Unified modeling language
ISBN:	0769529739, 9780769529738
ISSN:	2157-2305
Online-Zugang:	Volltext
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