This book presents the state-of-the-art in successfully engineered self-organizing systems. It goes further, too, to examine ways to balance design and self-organization in the context of applications. As demonstrated throughout, finding this balance helps to deal with diverse practical challenges. The case studies described illustrate the richness of the topic and provide guidance on its more intricate areas.

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.

Is it possible to guide the process of self-organisation towards specific patterns and outcomes? Wouldn’t this be self-contradictory? After all, a self-organising process assumes a transition into a more organised form, or towards a more structured functionality, in the absence of centralised control. Then how can we place the guiding elements so that they do not override rich choices potentially discoverable by an uncontrolled process? This book presents different approaches to resolving this paradox. In doing so, the presented studies address a broad range of phenomena, ranging from autopoietic systems to morphological computation, and from small-world networks to information cascades in swarms. A large variety of methods is employed, from spontaneous symmetry breaking to information dynamics to evolutionary algorithms, creating a rich spectrum reflecting this emerging field. Demonstrating several foundational theories and frameworks, as well as innovative practical implementations, Guided Self-Organisation: Inception, will be an invaluable tool for advanced students and researchers in a multiplicity of fields across computer science, physics and biology, including information theory, robotics, dynamical systems, graph theory, artificial life, multi-agent systems, theory of computation and machine learning.

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.

Autonomous robots may become our closest companions in the near future. While the technology for physically building such machines is already available today, a problem lies in the generation of the behavior for such complex machines. Nature proposes a solution: young children and higher animals learn to master their complex brain-body systems by playing. Can this be an option for robots? How can a machine be playful? The book provides answers by developing a general principle---homeokinesis, the dynamical symbiosis between brain, body, and environment---that is shown to drive robots to self- determined, individual development in a playful and obviously embodiment- related way: a dog-like robot starts playing with a barrier, eventually jumping or climbing over it; a snakebot develops coiling and jumping modes; humanoids develop climbing behaviors when fallen into a pit, or engage in wrestling-like scenarios when encountering an opponent. The book also develops guided self-organization, a new method that helps to make the playful machines fit for fulfilling tasks in the real world. The book provides two levels of presentation. Students and scientific researchers interested in the field of robotics, self-organization and dynamical systems theory may be satisfied by the in-depth mathematical analysis of the principle, the bootstrapping scenarios, and the emerging behaviors. But the book additionally comes with a robotics simulator inviting also the non- scientific reader to simply enjoy the fabulous world of playful machines by performing the numerous experiments.

The LNCS journal Transactions on Computational Science reflects recent developments in the field of Computational Science, conceiving the field not as a mere ancillary science but rather as an innovative approach supporting many other scientific disciplines. The journal focuses on original high-quality research in the realm of computational science in parallel and distributed environments, encompassing the facilitating theoretical foundations and the applications of large-scale computations and massive data processing. It addresses researchers and practitioners in areas ranging from aerospace to biochemistry, from electronics to geosciences, from mathematics to software architecture, presenting verifiable computational methods, findings, and solutions and enabling industrial users to apply techniques of leading-edge, large-scale, high performance computational methods. The 15th issue of the Transactions on Computational Science journal, edited by Cong-Vinh Phan, contains six invited papers on autonomic computing, with a special focus on formal engineering methods for nature-inspired computing systems. The papers give an in-depth overview of the area and a comprehensive evaluation of various methodologies for autonomic computing.

The multi-volume set LNAI 14169 until 14175 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2023, which took place in Turin, Italy, in September 2023. The 196 papers were selected from the 829 submissions for the Research Track, and 58 papers were selected from the 239 submissions for the Applied Data Science Track. The volumes are organized in topical sections as follows: Part I: Active Learning; Adversarial Machine Learning; Anomaly Detection; Applications; Bayesian Methods; Causality; Clustering. Part II: ​Computer Vision; Deep Learning; Fairness; Federated Learning; Few-shot learning; Generative Models; Graph Contrastive Learning. Part III: ​Graph Neural Networks; Graphs; Interpretability; Knowledge Graphs; Large-scale Learning. Part IV: ​Natural Language Processing; Neuro/Symbolic Learning; Optimization; Recommender Systems; Reinforcement Learning; Representation Learning. Part V: ​Robustness; Time Series; Transfer and Multitask Learning. Part VI: ​Applied Machine Learning; Computational Social Sciences; Finance; Hardware and Systems; Healthcare & Bioinformatics; Human-Computer Interaction; Recommendation and Information Retrieval. ​Part VII: Sustainability, Climate, and Environment.- Transportation & Urban Planning.- Demo.

The 4-volumes set of LNCS 13529, 13530, 13531, and 13532 constitutes the proceedings of the 31st International Conference on Artificial Neural Networks, ICANN 2022, held in Bristol, UK, in September 2022. The total of 255 full papers presented in these proceedings was carefully reviewed and selected from 561 submissions. ICANN 2022 is a dual-track conference featuring tracks in brain inspired computing and machine learning and artificial neural networks, with strong cross-disciplinary interactions and applications. Chapters “Learning Flexible Translation Between Robot Actions and Language Descriptions”, “Learning Visually Grounded Human-Robot Dialog in a Hybrid Neural Architecture” are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

This book constitutes the proceedings of the 16th IFIP TC8 International Conference on Computer Information Systems and Industrial Management, CISIM 2017, held in Bialystok, Poland, in June 2017. The 60 regular papers presented together with 5 keynotes were carefully reviewed and Selected from 85 submissions. They are organized in the following topical sections: algorithms; biometrics and pattern recognition applications; data analysis and information retrieval; engineering of enterprise software products; industrial management and other applications; modelling and optimization; various aspects of computer security.

Dynamic service-oriented environments (SOEs) are characterised by a large number of heterogeneous service components that are expected to support the business as a whole. The present work provides a negotiation-based approach to facilitate automated and multi-level service-level management in an SOE, where each component autonomously arranges its contribution to the whole operational goals. Evaluation experiments have shown an increased responsiveness and stability of an SOE in case of changes.