This book treats the computational use of social concepts as the focal point for the realisation of a novel class of socio-technical systems, comprising smart grids, public display environments, and grid computing. These systems are composed of technical and human constituents that interact with each other in an open environment. Heterogeneity, large scale, and uncertainty in the behaviour of the constituents and the environment are the rule rather than the exception. Ensuring the trustworthiness of such systems allows their technical constituents to interact with each other in a reliable, secure, and predictable way while their human users are able to understand and control them. "Trustworthy Open Self-Organising Systems" contains a wealth of knowledge, from trustworthy self-organisation mechanisms, to trust models, methods to measure a user's trust in a system, a discussion of social concepts beyond trust, and insights into the impact open self-organising systems will have on society.

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 collective systems consisting of social agents based on concepts like trust and reputation is explained. OC makes heavy use of learning and optimisation technologies; a compact overview of these technologies and related approaches to self-organising systems is provided. So far, OC literature has been published with the researcher in mind. Although the existing books have tried to follow a didactical concept, they remain basically collections of scientific papers. A comprehensive and systematic account of the OC ideas, methods, and achievements in the form of a textbook which lends itself to the newcomer in this field has been missing so far. The targeted reader of this book is the master student in Computer Science, Computer Engineering or Electrical Engineering - or any other newcomer to the field of Organic Computing with some technical or Computer Science background. Readers can seek access to OC ideas from different perspectives: OC can be viewed (1) as a „philosophy“ of adaptive and self-organising - life-like - technical systems, (2) as an approach to a more quantitative and formal understanding of such systems, and finally (3) a construction method for the practitioner who wants to build such systems. In this book, we first try to convey to the reader a feeling of the special character of natural and technical self-organising and adaptive systems through a large number of illustrative examples. Then we discuss quantitative aspects of such forms of organisation, and finally we turn to methods of how to build such systems for practical applications.

The two-volume set LNCS 10671 and 10672 constitutes the thoroughly refereed proceedings of the 16th International Conference on Computer Aided Systems Theory, EUROCAST 2017, held in Las Palmas de Gran Canaria, Spain, in February 2017. The 117 full papers presented were carefully reviewed and selected from 160 submissions. The papers are organized in topical sections on: pioneers and landmarks in the development of information and communication technologies; systems theory, socio-economic systems and applications; theory and applications of metaheuristic algorithms; stochastic models and applications to natural, social and technical systems; model-based system design, verification and simulation; applications of signal processing technology; algebraic and combinatorial methods in signal and pattern analysis; computer vision, deep learning and applications; computer and systems based methods and electronics technologies in medicine; intelligent transportation systems and smart mobility.

Self-organisation, self-regulation, self-repair and self-maintenance are promising conceptual approaches for dealing with complex distributed interactive software and information-handling systems. Self-organising applications dynamically change their functionality and structure without direct user intervention, responding to changes in requirements and the environment. This is the first book to offer an integrated view of self-organisation technologies applied to distributed systems, particularly focusing on multiagent systems. The editors developed this integrated book with three aims: to explain self-organisation concepts and principles, using clear definitions and a strong theoretical background; to examine how self-organising behaviour can be modelled, analysed and systematically engineered into agent behaviour; and to assess the types of problems that can be solved using self-organising multiagent systems. The book comprises chapters covering all three dimensions, synthesising up-to-date research work and the latest technologies and applications. The book offers dedicated chapters on concepts such as self-organisation, emergence in natural systems, software agents, stigmergy, gossip, cooperation and immune systems. The book then explains how to engineer artificial self-organising software, in particular it examines methodologies and middleware infrastructures. Finally, the book presents diverse applications of self-organising software, such as constraint satisfaction, trust management, image recognition and networking. The book will be of interest to researchers working on emergent phenomena and adaptive systems. It will also be suitable for use as a graduate textbook, with chapter summaries and exercises, and an accompanying website that includes teaching slides, exercise solutions and research project outlines. Self-organisation, self-regulation, self-repair and self-maintenance are promising conceptual approaches for dealing with complex distributed interactive software and information-handling systems. Self-organising applications dynamically change their functionality and structure without direct user intervention, responding to changes in requirements and the environment. This is the first book to offer an integrated view of self-organisation technologies applied to distributed systems, particularly focusing on multiagent systems. The editors developed this integrated book with three aims: to explain self-organisation concepts and principles, using clear definitions and a strong theoretical background; to examine how self-organising behaviour can be modelled, analysed and systematically engineered into agent behaviour; and to assess the types of problems that can be solved using self-organising multiagent systems. The book comprises chapters covering all three dimensions, synthesising up-to-date research work and the latest technologies and applications. The book offers dedicated chapters on concepts such as self-organisation, emergence in natural systems, software agents, stigmergy, gossip, cooperation and immune systems. The book then explains how to engineer artificial self-organising software, in particular it examines methodologies and middleware infrastructures. Finally, the book presents diverse applications of self-organising software, such as constraint satisfaction, trust management, image recognition and networking. The book will be of interest to researchers working on emergent phenomena and adaptive systems. It will also be suitable for use as a graduate textbook, with chapter summaries and exercises, and an accompanying website that includes teaching slides, exercise solutions and research project outlines.

'Advances in Intelligent Systems: Reviews' Vol. 1 Book Series is covering some design and architectural aspects related to intelligent systems and software. It ranges from the microarchitecture level via the system software level up to the application-specific architecture level. The book volume contains ten chapters written by 25 contributors from academia and industry from 8 countries: Colombia, Denmark, France, Germany, Italy, Japan, Romania and USA. The book will be a valuable tool for those who involved in research and development of various intelligent systems.

These transactions publish research in computer-based methods of computational collective intelligence (CCI) and their applications in a wide range of fields such as the semantic Web, social networks, and multi-agent systems. TCCI strives to cover new methodological, theoretical and practical aspects of CCI understood as the form of intelligence that emerges from the collaboration and competition of many individuals (artificial and/or natural). The application of multiple computational intelligence technologies, such as fuzzy systems, evolutionary computation, neural systems, consensus theory, etc., aims to support human and other collective intelligence and to create new forms of CCI in natural and/or artificial systems. This twenty-eight issue is a special issue with 11 selected papers from the International Conference on Agents and Artificial Intelligence, ICAART 2016 and 2017 editions.

Deep Learning for Robot Perception and Cognition introduces a broad range of topics and methods in deep learning for robot perception and cognition together with end-to-end methodologies. The book provides the conceptual and mathematical background needed for approaching a large number of robot perception and cognition tasks from an end-to-end learning point-of-view. The book is suitable for students, university and industry researchers and practitioners in Robotic Vision, Intelligent Control, Mechatronics, Deep Learning, Robotic Perception and Cognition tasks. - Presents deep learning principles and methodologies - Explains the principles of applying end-to-end learning in robotics applications - Presents how to design and train deep learning models - Shows how to apply deep learning in robot vision tasks such as object recognition, image classification, video analysis, and more - Uses robotic simulation environments for training deep learning models - Applies deep learning methods for different tasks ranging from planning and navigation to biosignal analysis

This book constitutes the thoroughly refereed proceedings of the Second International Conference on Machine Learning for Networking, MLN 2019, held in Paris, France, in December 2019. The 26 revised full papers included in the volume were carefully reviewed and selected from 75 submissions. They present and discuss new trends in deep and reinforcement learning, patternrecognition and classi cation for networks, machine learning for network slicingoptimization, 5G system, user behavior prediction, multimedia, IoT, securityand protection, optimization and new innovative machine learning methods, performanceanalysis of machine learning algorithms, experimental evaluations ofmachine learning, data mining in heterogeneous networks, distributed and decentralizedmachine learning algorithms, intelligent cloud-support communications,ressource allocation, energy-aware communications, software de ned networks,cooperative networks, positioning and navigation systems, wireless communications,wireless sensor networks, underwater sensor networks.

Trust, Digital Business and Technology: Issues and Challenges presents and discusses the main issues and challenges related to digital trust and information technologies. The subject of trust is relevant to both practitioners and researchers. It is widely recognized and confirmed that trust, especially mutual trust, when it is built at the right level, reduces the risk of interaction and increases the collaboration between partners. Readers will gain from this book theoretical and practical knowledge on digital trust; theoretically, well-grounded knowledge on digital trust and related concepts, empirically validated by practice. Most authors have taken innovative approaches to consider issues highlighting a selected aspect of the core theme of this book. The intended audiences of this book are professionals, scholars, and students.

As information handling systems get more and more complex, it becomes increasingly difficult to manage them using traditional approaches based on centralized and pre-defined control mechanisms. Over recent years, there has been a significant increase in taking inspiration from biology, the physical world, chemistry, and social systems to more efficiently manage such systems - generally based on the concept of self-organisation; this gave rise to self-organising applications. This book constitutes a reference and starting point for establishing the field of engineering self-organising applications. It comprises revised and extended papers presented at the Engineering Self-Organising Applications Workshop, ESOA 2003, held at AAMAS 2003 in Melbourne, Australia, in July 2003 and selected invited papers from leading researchers in self-organisation. The book is organized in parts on applications, natural metaphors (multi-cells and genetic algorithms, stigmergy, and atoms and evolution), artificial interaction mechanisms, middleware, and methods and tools.