Organic Computing

Doctoral Dissertation Colloquium 2014

Tomforde, Sven / Sick, Bernhard (Hrsg.)

Mit Beiträgen von Calma, Adrian / Edenhofer, Sarah / Gruhl, Christian / Ho, Nam / Kalkowski, Edgar / Kantert, Jan / Kieselmann, Olga / Kopal, Nils / Niemann, Sebastian / Prellwitz, Matthias / Reitmaier, Tobias / Schiendorfer, Alexander / Sick, Bernhard / Spiegelberg, Henning / Stein, Anthony / Tomforde, Sven / Wacker, Arno / Weis, Torben / Wildermann, Stefan

kassel university press, ISBN: 978-3-86219-832-0, 2014, 170 Seiten
(Intelligent Embedded Systems 4)

URN: urn:nbn:de:0002-38330

| Preis und lieferbare Formen -->

Inhalt: This book consists of twelve different contributions that reflect several aspects of OC research. Therefore, we introduced four major categories summarizing the contents of the contributions as well as describing the different aspects of OC research in general: (1) design and architectures, (2) trustworthiness, (3) self-learning, and (4) self-x properties.

Inhaltsverzeichnis

Tomforde, Sven /
Sick, Bernhard:
Preface

Invited Keynotes
Weis, Torben:Consistency in Distributed Self-Organizing Systems
Wildermann, Stefan:Design of Self-Adaptive Embedded Systems

Part I: Design and Architectures of Organic Computing Systems
Prellwitz, Matthias:Programming Abstractions for Organic Computing Applications
Spiegelberg, Henning:Organic Process Allocation for Distributed Embedded Systems
Ho, Nam:Towards An Efficient Architecture for Dynamically Reconfigurable Design

Part II: Technical Trust in Organic Computing Systems
Edenhofer, Sarah:Self-Organized Norm-Based Control in Open, Trusted Systems
Kantert, Jan:Norm-based System Control in Multi-Agent Systems
Schiendorfer, Alexander:Constraint Programming for Hierarchical Resource Allocation

Part III: Self-Learning Systems
Stein, Anthony:Neighborhood-based Interpolation for XCS Improvements
Reitmaier, Tobias /
Calma, Adrian:
Resp-kNN: A Semi-Supervised Classifier for Sparsely Labeled Data in the Field of Organic Computing
Gruhl, Christian:Self-Adapting Generative Modeling Techniques – A Basic Building Block for Many Organic Computing Techniques
Kalkowski, Edgar:Self-Extending Training Sets: Using Ontologies to Improve Machine Learning Performance

Part IV: Self-X Properties of Organic Computing Systems
Kopal, Nils /
Kieselmann, Olga /
Wacker, Arno:
Self-Organized Volunteer Computing
Niemann, Sebastian:Hint-based Online Optimization in Soft Real-Time Systems

Die Publikation ist in folgenden Formen erhältlich:

Volltext (pdf-Datei, ausdruckbar, kostenpflichtig - 8.10 MB) 20.00 Euro
(kostenfrei im Netz der Universität Kassel - Im Netz der Uni Kassel befinden Sie sich, wenn Sie z.B. an einem Rechner im ITS, Ihrem Arbeitsplatz an der Uni oder auch in der Multimediathek der Bibliothek befinden.)
PDF erwerben (download) - Achtung kostenpflichtig, da Sie sich zur Zeit nicht im Netz der Uni-Kassel befinden