Springer Robust Intelligent Systems

Using artificial intelligence and robustness as a unifying theme, this book comments on the fundamental strategies found in nature and how an understanding of these can be used to further research into general design principles for artificial intelligence. From the Back Cover Robustness is an intriguing phenomenon in many complex intelligent systems, natural and artificial alike. This book investigates the relevance of robustness in a modern intelligent computing context, where many systems take inspiration from fundamental problem-solving strategies found in nature such as redundancy, granularity, adaptation, repair, and self-healing for creating robust systems. The book explores the value these strategies may have as general design principles in a diverse range of areas including the computer technology underlying many intelligent systems, and also systems and applications inspired by biology, artificial intelligence, and intelligent space exploration. The topics covered include computer hardware and software, networks and protocols, brain-computer interfaces, biological networks and immune systems, humanoid robotics, image processing, artificial neural networks, genetic algorithms, chaos theory, and other soft computing techniques, as well as space system design and bio-regenerative life support systems. As modern information technology and modern computing are integral to many areas of human life and are used in increasingly more sophisticated and challenging ways, by looking at the relevance and importance of robustness as found in nature as a design principle for intelligent systems, this book provides a unique resource for practitioners in a wide variety of fields.