Self Adaptive Systems For Machine Intelligence

A concise and practical introduction to the foundations and engineering principles of self-adaptation Though it has recently gained significant momentum, the topic of self-adaptation remains largely under-addressed in academic and technical literature. This book changes that. Using a systematic and holistic approach, An Introduction to Self-adaptive Systems: A Contemporary Software Engineering Perspective provides readers with an accessible set of basic principles, engineering foundations, and applications of self-adaptation in software-intensive systems. It places self-adaptation in the context of techniques like uncertainty management, feedback control, online reasoning, and machine learning while acknowledging the growing consensus in the software engineering community that self-adaptation will be a crucial enabling feature in tackling the challenges of new, emerging, and future systems. The author combines cutting-edge technical research with basic principles and real-world insights to create a practical and strategically effective guide to self-adaptation. He includes features such as: An analysis of the foundational engineering principles and applications of self-adaptation in different domains, including the Internet-of-Things, cloud computing, and cyber-physical systems End-of-chapter exercises at four different levels of complexity and difficulty An accompanying author-hosted website with slides, selected exercises and solutions, models, and code Perfect for researchers, students, teachers, industry leaders, and practitioners in fields that directly or peripherally involve software engineering, as well as those in academia involved in a class on self-adaptivity, this book belongs on the shelves of anyone with an interest in the future of software and its engineering.

This book will advance the understanding and application of self-adaptive intelligent systems; therefore it will potentially benefit the long-term goal of replicating certain levels of brain-like intelligence in complex and networked engineering systems. It will provide new approaches for adaptive systems within uncertain environments. This will provide an opportunity to evaluate the strengths and weaknesses of the current state-of-the-art of knowledge, give rise to new research directions, and educate future professionals in this domain. Self-adaptive intelligent systems have wide applications from military security systems to civilian daily life. In this book, different application problems, including pattern recognition, classification, image recovery, and sequence learning, will be presented to show the capability of the proposed systems in learning, memory, and prediction. Therefore, this book will also provide potential new solutions to many real-world applications.

The book intends to cover various problematic aspects of emerging smart computing and self-adapting technologies comprising of machine learning, artificial intelligence, deep learning, robotics, cloud computing, fog computing, data mining algorithms, including emerging intelligent and smart applications related to these research areas. Further coverage includes implementation of self-adaptation architecture for smart devices, self-adaptive models for smart cities and self-driven cars, decentralized self-adaptive computing at the edge networks, energy-aware AI-based systems, M2M networks, sensors, data analytics, algorithms and tools for engineering self-adaptive systems, and so forth. Acts as guide to Self-healing and Self-adaptation based fully automatic future technologies Discusses about Smart Computational abilities and self-adaptive systems Illustrates tools and techniques for data management and explains the need to apply, and data integration for improving efficiency of big data Exclusive chapter on the future of self-stabilizing and self-adaptive systems of systems Covers fields such as automation, robotics, medical sciences, biomedical and agricultural sciences, healthcare and so forth This book is aimed researchers and graduate students in machine learning, information technology, and artificial intelligence.

The carefully reviewed papers in this state-of-the-art survey describe a wide range of approaches coming from different strands of software engineering, and look forward to future challenges facing this ever-resurgent and exacting field of research.

A concise and practical introduction to the foundations and engineering principles of self-adaptation Though it has recently gained significant momentum, the topic of self-adaptation remains largely under-addressed in academic and technical literature. This book changes that. Using a systematic and holistic approach, An Introduction to Self-adaptive Systems: A Contemporary Software Engineering Perspective provides readers with an accessible set of basic principles, engineering foundations, and applications of self-adaptation in software-intensive systems. It places self-adaptation in the context of techniques like uncertainty management, feedback control, online reasoning, and machine learning while acknowledging the growing consensus in the software engineering community that self-adaptation will be a crucial enabling feature in tackling the challenges of new, emerging, and future systems. The author combines cutting-edge technical research with basic principles and real-world insights to create a practical and strategically effective guide to self-adaptation. He includes features such as: An analysis of the foundational engineering principles and applications of self-adaptation in different domains, including the Internet-of-Things, cloud computing, and cyber-physical systems End-of-chapter exercises at four different levels of complexity and difficulty An accompanying author-hosted website with slides, selected exercises and solutions, models, and code Perfect for researchers, students, teachers, industry leaders, and practitioners in fields that directly or peripherally involve software engineering, as well as those in academia involved in a class on self-adaptivity, this book belongs on the shelves of anyone with an interest in the future of software and its engineering.

A major challenge for modern software systems is to become more cost-effective, while being versatile, flexible, resilient, energy-efficient, customizable, and configurable when reacting to run-time changes that may occur within the system itself, its environment or requirements. One of the most promising approaches to achieving such properties is to equip the software system with self-adaptation capabilities. Despite recent advances in this area, one key aspect that remains to be tackled in depth is the provision of assurances. Originating from a Dagstuhl seminar held in December 2013, this book constitutes the third volume in the series “Software Engineering for Self-Adaptive Systems”, and looks specifically into the provision of assurances. Opening with an overview chapter on Research Challenges, the book presents 13 further chapters written and carefully reviewed by internationally leading researchers in the field. The book is divided into topical sections on research challenges, evaluation, integration and coordination, and reference architectures and platforms.

Although the self-adaptability of systems has been studied in a wide range of disciplines, from biology to robotics, only recently has the software engineering community recognized its key role in enabling the development of self-adaptive systems that are able to adapt to internal faults, changing requirements, and evolving environments. The 15 carefully reviewed papers included in this state-of-the-art survey were presented at the International Seminar on "Software Engineering for Self-Adaptive Systems", held in Dagstuhl Castle, Germany, in October 2010. Continuing the course of the first book of the series on "Software Engineering for Self-Adaptive Systems" the collection of papers in this second volume comprises a research roadmap accompanied by four elaborating working group papers. Next there are two parts - with three papers each - entitled "Requirements and Policies" and "Design Issues"; part four of the book contains four papers covering a wide range of "Applications".

Self-adaptive software evaluates its own behavior and changes its behavior when the evaluation indicates that the software does not accomplish what it is intended to do or when better functionality or better performance is possible. The self-adaptive approach in software engineering builds on well-known features like the use of errors and the handling of exceptions in languages like Lisp or Java and aims at improving the robustness of software systems by gradually adding new features of self-adaption and autonomity. This book originates from the First International Workshop on Self-Adaptive Software, IWSAS 2000, held in Oxford, UK in April 2000. The revised full papers presented in the volume together with an introductory survey by the volume editors assess the state of the art in this emerging new field and set the scene for future research and development work.

Although the self-adaptability of systems has been studied in a wide range of disciplines, from biology to robotics, only recently has the software engineering community recognised its key role in enabling the development of future software systems that are able to self-adapt to changes that may occur in the system, its requirements, or the environment in which it is deployed. The 12 carefully reviewed papers included in thisstate-of-the-art survey originate from the International Seminar on Software Engineering for Self-Adaptive Systems, held in Dagstuhl Castle, Germany, in January 2008. They examine the current state-of-the-art in the field, describing a wide range of approaches coming from different strands of software engineering, and present future challenges facing this ever-resurgent and challenging field of research. Also included in this book is an invited roadmap paper on theresearch challenges facing self-adaptive systems withinthe area of software engineering, based on discussionsat the Dagstuhl Seminar and put together by several of its participants. The papers have been divided into topical sections onarchitecture-based self-adaptation, context-aware and model-driven self-adaptation, and self-healing. These are preceded by three research roadmap papers.

The 18 revised full papers presented in this book together with an introductory survey were carefully reviewed and constitute the documentation of the Second International Workshop on Self-adaptive Software, IWSAS 2001, held in Balatonfüred, Hungary in May 2001. Self-adaptive software evaluates its own behavior and changes it when the evaluation indicates that the software does not accomplish what it is intended to do or when better functionality or better performance is possible. The self-adaptive approach in software engineering builds on well known dynamic features familiar to Lisp or Java programmes and aims at improving the robustness of software systems by gradually adding new features of self-adaption or autonomy.