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This text constitutes the proceedings from the IEEE International Conference on Systems, Man and Cybernetics (SMC), which was held in 1999. Topics covered include systems science, soft computing and robotics.
Discover the emerging science and engineering of System of Systems Many challenges of the twenty-first century, such as fossil fuel energy resources, require a new approach. The emergence of System of Systems (SoS) and System of Systems Engineering (SoSE) presents engineers and professionals with the potential for solving many of the challenges facing our world today. This groundbreaking book brings together the viewpoints of key global players in the field to not only define these challenges, but to provide possible solutions. Each chapter has been contributed by an international expert, and topics covered include modeling, simulation, architecture, the emergence of SoS and SoSE, net-centricity, standards, management, and optimization, with various applications to defense, transportation, energy, the environment, healthcare, service industry, aerospace, robotics, infrastructure, and information technology. The book has been complemented with several case studies—Space Exploration, Future Energy Resources, Commercial Airlines Maintenance, Manufacturing Sector, Service Sector, Intelligent Transportation, Future Combat Missions, Global Earth Observation System of Systems project, and many more—to give readers an understanding of the real-world applications of this relatively new technology. System of Systems Engineering is an indispensable resource for aerospace and defense engineers and professionals in related fields.
Due to inherent limitations in human sensing organs, most data collected for various purposes contain uncertainties. Even at the rare occasions when accurate data are available, the truthful predictions derived on the data tend to create chaotic consequences. So, to effectively process and make sense out of available data, we need methods to deal with uncertainty inherently existing inside the data. The intent of this monograph is to explore the fundamental theory, methods, and techniques of practical application of grey systems theory, initiated by Professor Deng Julong in 1982. This volume presents most of the recent advances of the theory accomplished by scholars from around the world. From studying this book, the reader will not only acquire an overall knowledge of this new theory but also be able to follow the most current research activities. All examples presented are based on practical applications of the theory when urgent real-life problems had to be addressed. Last but not the least, this book concludes with three appendices. The first one compares grey systems theory and interval analysis while revealing the fact that interval analysis is a part of grey mathematics. The second appendix presents an array of different approaches of studying uncertainties. And, the last appendix shows how uncertainties appear using general systems approach.
State-of-the-art robotics research on such topics as manipulation, motion planning, micro-robotics, distributed systems, autonomous navigation, and mapping. Robotics: Science and Systems IV spans a wide spectrum of robotics, bringing together researchers working on the foundations of robotics, robotics applications, and analysis of robotics systems. This volume presents the proceedings of the fourth annual Robotics: Science and Systems conference, held in 2008 at the Swiss Federal Institute of Technology in Zurich. The papers presented cover a range of topics, including computer vision, mapping, terrain identification, distributed systems, localization, manipulation, collision avoidance, multibody dynamics, obstacle detection, microrobotic systems, pursuit-evasion, grasping and manipulation, tracking, spatial kinematics, machine learning, and sensor networks as well as such applications as autonomous driving and design of manipulators for use in functional-MRI. The conference and its proceedings reflect not only the tremendous growth of robotics as a discipline but also the desire in the robotics community for a flagship event at which the best of the research in the field can be presented.
Computational Intelligence: An Introduction, Second Edition offers an in-depth exploration into the adaptive mechanisms that enable intelligent behaviour in complex and changing environments. The main focus of this text is centred on the computational modelling of biological and natural intelligent systems, encompassing swarm intelligence, fuzzy systems, artificial neutral networks, artificial immune systems and evolutionary computation. Engelbrecht provides readers with a wide knowledge of Computational Intelligence (CI) paradigms and algorithms; inviting readers to implement and problem solve real-world, complex problems within the CI development framework. This implementation framework will enable readers to tackle new problems without any difficulty through a single Java class as part of the CI library. Key features of this second edition include: A tutorial, hands-on based presentation of the material. State-of-the-art coverage of the most recent developments in computational intelligence with more elaborate discussions on intelligence and artificial intelligence (AI). New discussion of Darwinian evolution versus Lamarckian evolution, also including swarm robotics, hybrid systems and artificial immune systems. A section on how to perform empirical studies; topics including statistical analysis of stochastic algorithms, and an open source library of CI algorithms. Tables, illustrations, graphs, examples, assignments, Java code implementing the algorithms, and a complete CI implementation and experimental framework. Computational Intelligence: An Introduction, Second Edition is essential reading for third and fourth year undergraduate and postgraduate students studying CI. The first edition has been prescribed by a number of overseas universities and is thus a valuable teaching tool. In addition, it will also be a useful resource for researchers in Computational Intelligence and Artificial Intelligence, as well as engineers, statisticians, operational researchers, and bioinformaticians with an interest in applying AI or CI to solve problems in their domains. Check out http://www.ci.cs.up.ac.za for examples, assignments and Java code implementing the algorithms.