Realizing Complex Integrated Systems
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Realizing Complex Integrated Systems
The creation of complex integrated systems is, in itself, complex. It requires immense planning and a large team of people with diverse backgrounds based in dispersed geographical locations (and countries) supposedly working to a coordinated schedule and cost. The systems engineering task is not new, but recent scales most definitely are. The world is now capable of designing and manufacturing systems whose complexity was not considered possible 10 years ago. While many are trained to think in terms of a complete system, where ‘everything’ is designed and produced by a single project team, today such systems involve integrating subsystems and components (which are also complex) that have been developed by other project teams. Inevitably, this introduces additional complexities, involving elements out of the direct control of the project, but which are essential to its overall success. In addition to traditional systems engineering topics of hardware and software design, testability, and manufacturability, there are wider issues to be contemplated: project planning; communication language (an issue for international teams); units of measure (imperial vs. metric) used across members of the team; supply chains (pandemics, military action, and natural disasters); legal issues based on place of production and sale; the ethics associated with target use; and the threat of cyberattack. This book is the first attempt to bring many of these issues together to highlight the complexities that need to be considered in modern system design. It is neither exhaustive nor comprehensive, but it gives pointers to the topics for the reader to follow up on in more detail.
An Introduction to Self-adaptive Systems
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.
Multiagent Robotic Systems
Providing a guided tour of the pioneering work and major technical issues, Multiagent Robotic Systems addresses learning and adaptation in decentralized autonomous robots. Its systematic examination demonstrates the interrelationships between the autonomy of individual robots and the emerged global behavior properties of a group performing a cooperative task. The author also includes descriptions of the essential building blocks of the architecture of autonomous mobile robots with respect to their requirement on local behavioral conditioning and group behavioral evolution. After reading this book you will be able to fully appreciate the strengths and usefulness of various approaches in the development and application of multiagent robotic systems. It covers: Why and how to develop and experimentally test the computational mechanisms for learning and evolving sensory-motor control behaviors in autonomous robots How to design and develop evolutionary algorithm-based group behavioral learning mechanisms for the optimal emergence of group behaviors How to enable group robots to converge to a finite number of desirable task states through group learning What are the effects of the local learning mechanisms on the emergent global behaviors How to use decentralized, self-organizing autonomous robots to perform cooperative tasks in an unknown environment Earlier works have focused primarily on how to navigate in a spatially unknown environment, given certain predefined motion behaviors. What is missing, however, is an in-depth look at the important issues on how to effectively obtain such behaviors in group robots and how to enable behavioral learning and adaptation at the group level. Multiagent Robotic Systems examines the key methodological issues and gives you an understanding of the underlying computational models and techniques for multiagent systems.