Nature-inspired VLSI circuit technology offers unique approach for studying, analyzing, designing, and implementing VLSI circuits through perception, reasoning and action mimicking the nature. Such circuit technology covers various aspects of nature-inspired VLSI circuit design techniques, such as the design rule bases, design principles, computing and information processing algorithms, sensing and interfacing techniques, energy harvesting and power management.

This book constitutes, together with its compagnion LNCS 1606, the refereed proceedings of the International Work-Conference on Artificial and Neural Networks, IWANN'99, held in Alicante, Spain in June 1999. The 91 revised papers presented were carefully reviewed and selected for inclusion in the book. This volume is devoted to applications of biologically inspired artificial neural networks in various engineering disciplines. The papers are organized in parts on artificial neural nets simulation and implementation, image processing, and engineering applications.

Beginning in the mid 1980's, VLSI technology had begun to advance in two directions. Pushing the limit of integration, ULSI (Ultra Large Scale Integration) represents the frontier of the semiconductor processing technology in the campaign to conquer the submicron realm. The application of ULSI, however, is at present largely confined in the area of memory designs, and as such, its impact on traditional, microprocessor-based system design is modest. If advancement in this direction is merely a natural extrapolation from the previous integration generations, then the rise of ASIC (Application-Specific Integrated Circuit) is an unequivocal signal that a directional change in the discipline of system design is in effect. In contrast to ULSI, ASIC employs only well proven technology, and hence is usually at least one generation behind the most advanced processing technology. In spite of this apparent disadvantage, ASIC has become the mainstream of VLSI design and the technology base of numerous entrepreneurial opportunities ranging from PC clones to supercomputers. Unlike ULSI whose complexity can be hidden inside a memory chip or a standard component and thus can be accommodated by traditional system design methods, ASIC requires system designers to master a much larger body of knowledge spanning from processing technology and circuit techniques to architecture principles and algorithm characteristics. Integrating knowledge in these various areas has become the precondition for integrating devices and functions into an ASIC chip in a market-oriented environment. But knowledge is of two kinds.

This book is a tribute to Julian Francis Miller’s ideas and achievements in computer science, evolutionary algorithms and genetic programming, electronics, unconventional computing, artificial chemistry and theoretical biology. Leading international experts in computing inspired by nature offer their insights into the principles of information processing and optimisation in simulated and experimental living, physical and chemical substrates. Miller invented Cartesian Genetic Programming (CGP) in 1999, from a representation of electronic circuits he devised with Thomson a few years earlier. The book presents a number of CGP’s wide applications, including multi-step ahead forecasting, solving artificial neural networks dogma, approximate computing, medical informatics, control engineering, evolvable hardware, and multi-objective evolutionary optimisations. The book addresses in depth the technique of ‘Evolution in Materio’, a term coined by Miller and Downing, using a range of examples of experimental prototypes of computing in disordered ensembles of graphene nanotubes, slime mould, plants, and reaction diffusion chemical systems. Advances in sub-symbolic artificial chemistries, artificial bio-inspired development, code evolution with genetic programming, and using Reed-Muller expansions in the synthesis of Boolean quantum circuits add a unique flavour to the content. The book is a pleasure to explore for readers from all walks of life, from undergraduate students to university professors, from mathematicians, computer scientists and engineers to chemists and biologists.

This book presents a comprehensive reference source for dynamic and innovative research in the field of cyber security, focusing on nature-inspired research and applications. The authors present the design and development of future-ready cyber security measures, providing a critical and descriptive examination of all facets of cyber security with a special focus on recent technologies and applications. The book showcases the advanced defensive cyber security mechanism that is a requirement in the industry and highlights measures that provide efficient and fast solutions. The authors explore the potential of AI-based and nature-inspired based computing compatibilities in establishing an adaptive defense mechanism system. The book focuses on current research while highlighting the empirical results along with theoretical concepts to provide a reference for students, researchers, scholars, professionals, and practitioners in the field of cyber security and analytics. This book features contributions from leading scholars from all over the world.

The second of a two-volume set, this book constitutes the refereed proceedings of the Second International Work-Conference on the Interplay between Natural and Artificial Computation, IWINAC 2007, held in La Manga del Mar Menor, Spain in June 2007. It contains all the contributions connected with biologically inspired methods and techniques for solving AI and knowledge engineering problems in different application domains.

"Nature-inspired" includes, roughly speaking, "bio-inspired"+"physical-inspired"+"social-inspired"+ and so on. This book contains highly original contributions about how nature is going to shape networking systems of the future. Hence, it focuses on rigorous approaches and cutting-edge solutions, which encompass three classes of major methods: 1) Those that take inspiration from nature for the development of novel problem solving techniques; 2) Those that are based on the use of networks to synthesize natural phenomena; and 3) Those that employ natural materials to compute or communicate.

Robotics and Automation in Industry 4.0 explores the transformative role of robotics, automation, and emerging technologies in the modern industrial landscape. The book is divided into four comprehensive sections, each focusing on key areas of Industry 4.0. These are: 1) Robotics: Applications and Advancements, 2) Renewable Energy Applications, 3), FinTech, and 4) Multidisciplinary approaches. It compiles 13 chapters offering insights into the latest advancements and provides practical guidance for navigating the evolving industrial landscape.

This contributed volume book aims at discussing transdisciplinary approaches to address common problems. By working transdisciplinarily, researchers coming from different disciplines can work jointly using a shared conceptual framework bringing together disciplinary-specific theories and concepts. There are numerous barriers that can obstruct effective communication between different cultures, communities, religions and geographies. This book shows that through bringing together different disciplines, researchers not only can surpass these barriers but can effectively produce new venues of thought that can positively affect the development and evolution of research and education. The book discusses new and emerging applications of knowledge produced by transdisciplinary efforts and covers the interplay of many disciplines, including agriculture, economics, mathematics, engineering, industry, information technology, marketing, nanoscience, neuroscience, space exploration, human-animal relationships, among others. Consequently, it also covers the relationship between art and science, as one of the most remarkable transdisciplinary approaches that paves the way for new methods in engineering, design, architecture and many other fields.

As computing devices proliferate, demand increases for an understanding of emerging computing paradigms and models based on natural phenomena. Neural networks, evolution-based models, quantum computing, and DNA-based computing and simulations are all a necessary part of modern computing analysis and systems development. Vast literature exists on these new paradigms and their implications for a wide array of applications. This comprehensive handbook, the first of its kind to address the connection between nature-inspired and traditional computational paradigms, is a repository of case studies dealing with different problems in computing and solutions to these problems based on nature-inspired paradigms. The "Handbook of Nature-Inspired and Innovative Computing: Integrating Classical Models with Emerging Technologies" is an essential compilation of models, methods, and algorithms for researchers, professionals, and advanced-level students working in all areas of computer science, IT, biocomputing, and network engineering.