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Organic Computing
This book consists of fourteen different contributions that can be grouped into five major categories reflecting the different aspects of current OC research in general: (1) trustworthiness, (2) swarm behaviour, (3) security and testing, (4) self-learning, and (5) hardware aspects.
Organic Computing
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.
Organic Computing – Technical Systems for Survival in the Real World
This book is a comprehensive introduction into Organic Computing (OC), presenting systematically the current state-of-the-art in OC. It starts with motivating examples of self-organising, self-adaptive and emergent systems, derives their common characteristics and explains the fundamental ideas for a formal characterisation of such systems. Special emphasis is given to a quantitative treatment of concepts like self-organisation, emergence, autonomy, robustness, and adaptivity. The book shows practical examples of architectures for OC systems and their applications in traffic control, grid computing, sensor networks, robotics, and smart camera systems. The extension of single OC systems into ...
Architecture of Computing Systems
This book constitutes the proceedings of the 36th International Conference on Architecture of Computing Systems, ARCS 2023, which took place in Athens, Greece, in June 2023. The 18 full papers in this volume were carefully reviewed and selected from 35 submissions. ARCS provides a platform covering newly emerging and cross-cutting topics, such as autonomous and ubiquitous systems, reconfigurable computing and acceleration, neural networks and artificial intelligence. The selected papers cover a variety of topics from the ARCS core domains, including energy efficiency, applied machine learning, hardware and software system security, reliable and fault-tolerant systems and organic computing. Back to top
Organic Computing
This book presents the results of the OC-DDC 2017. Successful participants have been invited to extend their abstracts submitted to the event towards a full book chapter by taking reviews and feedback received at the event in Bochum into account. Seven of the participants prepared a contribution to this book, helped to perform a sophisticated review process, and finally came up with interesting articles summarising their current work in the context of Organic Computing. Hence, the book also gives an overview of corresponding research activities in the field in Germany for the year 2017. The collection of contributions reflects the diversity of the different aspects of Organic Computing. Furthermore, group discussions during the OC-DDC resulted in a contribution that aggregates the ideas of the participants related to applied machine learning for Organic Computing systems.Keine Angaben
Organic Computing
This book presents the results of the OC-DDC 2018. Successful participants have been invited to extend their abstracts submitted to the event towards a full book chapter by taking reviews and feedback received at the event in Wurzburg into account. The participants prepared an initial extended abstract, helped to perform a sophisticated review process, and finally came up with interesting articles summarising their current work in the context of Organic Computing. Hence, the book also gives an overview of corresponding research activities in the field in Germany for the year 2018. The collection of contributions reflects the diversity of the different aspects of Organic Computing. In the following, we outline the contributions contained in this book.
Technical Safety, Reliability and Resilience
This book provides basics and selected advanced insights on how to generate reliability, safety and resilience within (socio) technical system developments. The focus is on working definitions, fundamental development processes, safety development processes and analytical methods on how to support such schemes. The method families of Hazard Analyses, Failure Modes and Effects Analysis and Fault Tree Analysis are explained in detail. Further main topics include semiformal graphical system modelling, requirements types, hazard log, reliability prediction standards, techniques and measures for reliable hardware and software with respect to systematic and statistical errors, and combination options of methods. The book is based on methods as applied during numerous applied research and development projects and the support and auditing of such projects, including highly safety-critical automated and autonomous systems. Numerous questions and answers challenge students and practitioners.
Autonomic and Trusted Computing
This book constitutes the refereed procedings of the 6th International Conference on Autonomic and Trusted Computing, ATC 2009, held in Brisbane, Australia, in July 2009, co-located with UIC 2009, the 6th International Conference on Ubiquitous Intelligence and Computing. The 17 revised full papers presented together with one invited paper and one keynote talk were carefully reviewed and selected from 52 submissions. The regular papers are organized in topical sections on organic and autonomic computing, trusted computing, wireless sensor networks, and trust.
A Holistic, Decision-Theoretic Framework for Pool-Based Active Learning
Efficient labeling is an important topic in machine learning research as classifiers need labeled data. Whereas unlabeled data is easily gathered, labeling is exhausting, time-consuming, or expensive and should, therefore, be reduced to a minimum. Active learning aims to actively select useful, unlabeled instances for label acquisition to reduce the labeling effort while providing labeled training data such that the classifier performs well. This thesis proposes Probabilistic Active Learning, a holistic, decision-theoretic framework for active learning that enables optimization for every performance measure and classifier. Using the holistic mathematical description, we can define an upper b...
Artificial Intelligence and Soft Computing
The two-volume set LNAI 14125 and 14126 constitutes the refereed conference proceedings of the 22nd International Conference on Artificial Intelligence and Soft Computing, ICAISC 2023, held in Zakopane, Poland, during June 18–22, 2023. The 84 revised full papers presented in these proceedings were carefully reviewed and selected from 175 submissions. The papers are organized in the following topical sections: Part I: Neural Networks and Their Applications; Evolutionary Algorithms and Their Applications; and Artificial Intelligence in Modeling and Simulation. Part II: Computer Vision, Image and Speech Analysis; Various Problems of Artificial Intelligence; Bioinformatics, Biometrics and Medical Applications; and Data Mining and Pateern Classification.
