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Introduction to Evolvable Hardware: A Practical Guide for Designing Self-Adaptive Systems provides a fundamental introduction for engineers, designers, and managers involved in the development of adaptive, high reliability systems. It also introduces the concepts of evolvable hardware (EHW) to new researchers in a structured way. With this practical book, you’ll be able to quickly apply the techniques presented to existing design problems.
This book covers the basic theory, practical details and advanced research of the implementation of evolutionary methods on physical substrates. Most of the examples are from electronic engineering applications, including transistor-level design and system-level implementation. The authors present an overview of the successes achieved, and the book will act as a point of reference for both academic and industrial researchers.
Evolvable hardware (EHW) refers to hardware whose architecture/structure and functions change dynamically and autonomously in order to improve its performance in carrying out tasks. The only single resource presenting both the fundamentals, and the latest advances in the field, this book teaches the basics of reconfigurable devices, why they are necessary and how they are designed.
This book constitutes the refereed proceedings of the 7th International Conference on Evolvable Systems, ICES 2007, held in Wuhan, China, in September 2007. The 41 revised full papers collected in this volume are organized in topical sections on digital hardware evolution, analog hardware evolution, bio-inspired systems, mechanical hardware evolution, evolutionary design, evolutionary algorithms in hardware design, and hardware implementation of evolutionary algorithms.
Evolvable Hardware (EHW) has emerged as a sub-domain of artificial evolution represented by a design methodology (consortium of methods) involving the application of Evolutionary Algorithms (EA) to the synthesis of digital and analogue electronic circuits and systems. Nevertheless, the most benefit for the society and indeed most revolutionizing application of EA is its hardware implementation leading to the EHW. These new EA based methodologies led to a new type of machines that is evolved to attain a desired behaviour, which means they have a behavioural computational intelligence. EHW is a special case of the adaptive hardware, namely being strongly related to the Adaptive Systems (AS) and the Adaptive Hardware (AH). The book presents a careful selection of the field that very well reflects the breadth of this high technology and its terminology and applications in context of the AS/AH. The harmonious symbiosis of the engineering approach and the accurate scientific methodology features the aspects of highly relevant and practical design principles governing the development of EHW and its connections with AS/AH. This book is both attractive and useful for everybody interested in the design and analysis of EHW in context of AS/AH and implementation of real time adaptive hardware hybrid intelligent systems.
On behalf of the ICES 2001 Conference Committee, it is our pleasure to present to you the proceedings of the fourth International Conference on Evolvable S- tems: From Biology to Hardware, ICES 2001, held in Tokyo, Japan, on 3-5 - tober 2001, addressing the latest developments and discussing challenges facing the ?eld of evolvable systems. The idea of evolving machines, whose origins can be traced back to the - bernetics movement of the 1940s and the 1950s, has recently re-emerged in the form of the nascent ?eld of bio-inspired systems and evolvable hardware. Foll- ing the workshop, Towards Evolvable Hardware, which took place in Lausanne, Switzerland, in October 1995, the First International Conference on Evolvable Systems: From Biology to Hardware (ICES96), was held at the Electrotech- cal Laboratory (MITI), Tsukuba, Japan, in October 1996. The second and the third International Conferences on Evolvable Systems: From Biology to Ha- ware (ICES98 and ICES 2000) were respectively held in Lausanne in September 1998, and in Edinburgh in April 2000. Following the success of these past events, ICES 2001 was dedicated to the promotion and advancement of all aspects of evolvable systems, including ha- ware, software, algorithms, and applications. By bringing together researchers who use biologically inspired concepts to implement real systems in arti?cial - telligence, arti?cial life, robotics, VLSI design, and related domains, ICES 2001 reunited this burgeoning community.
At the beginning of the 1990s research started in how to combine soft comput ing with reconfigurable hardware in a quite unique way. One of the methods that was developed has been called evolvable hardware. Thanks to evolution ary algorithms researchers have started to evolve electronic circuits routinely. A number of interesting circuits - with features unreachable by means of con ventional techniques - have been developed. Evolvable hardware is quite pop ular right now; more than fifty research groups are spread out over the world. Evolvable hardware has become a part of the curriculum at some universi ties. Evolvable hardware is being commercialized and there are specialized conferences devoted to evolvable hardware. On the other hand, surprisingly, we can feel the lack of a theoretical background and consistent design methodology in the area. Furthermore, it is quite difficult to implement really innovative and practically successful evolvable systems using contemporary digital reconfigurable technology.
Reconfigurable circuit devices have opened up a fundamentally new way of creating adaptable systems. Combined with artificial evolution, reconfigurable circuits allow an elegant adaptation approach to compensating for changes in the distribution of input data, computational resource errors, and variations in resource requirements. Referred to as "Evolvable Hardware" (EHW), this paradigm has yielded astonishing results for traditional engineering challenges and has discovered intriguing design principles, which have not yet been seen in conventional engineering. In this thesis, we present new and fundamental work on Evolvable Hardware motivated by the insight that Evolvable Hardware needs to compensate for events with different change rates. To solve the challenge of different adaptation speeds, we propose a unified adaptation approach based on multi-objective evolution, evolving and propagating candidate solutions that are diverse in objectives that may experience radical changes. Focusing on algorithmic aspects, we enable Cartesian Genetic Programming (CGP) model, which we are using to encode Boolean circuits, for multi-objective optimization by introducing a meaningful recombination operator. We improve the scalability of CGP by objectives scaling, periodization of local- and global-search algorithms, and the automatic acquisition and reuse of subfunctions using age- and cone-based techniques. We validate our methods on the applications of adaptation of hardware classifiers to resource changes, recognition of muscular signals for prosthesis control and optimization of processor caches.
Biology has inspired electronics from the very beginning: the machines that we now call computers are deeply rooted in biological metaphors. Pioneers such as Alan Turing and John von Neumann openly declared their aim of creating arti?cial machines that could mimic some of the behaviors exhibited by natural organisms. Unfortunately, technology had not progressed enough to allow them to put their ideas into practice. The 1990s saw the introduction of programmable devices, both digital (FP- GAs) and analogue (FPAAs). These devices, by allowing the functionality and the structure of electronic devices to be easily altered, enabled researchers to endow circuits with some of the same versatility exhibited by biological entities and sparked a renaissance in the ?eld of bio-inspired electronics with the birth of what is generally known as evolvable hardware. Eversince,the?eldhasprogressedalongwiththetechnologicalimprovements and has expanded to take into account many di?erent biological processes, from evolution to learning, from development to healing. Of course, the application of these processes to electronic devices is not always straightforward (to say the least!), but rather than being discouraged, researchers in the community have shown remarkable ingenuity, as demostrated by the variety of approaches presented at this conference and included in these proceedings.
Computational Intelligence: A Compendium presents a well structured overview about this rapidly growing field with contributions from leading experts in Computational Intelligence. The main focus of the compendium is on applied methods, tried-and-proven as being effective to realworld problems, which is especially useful for practitioners, researchers, students and also newcomers to the field. This state-of- handbook-style book has contributions by leading experts.