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.

This monograph presents key method to successfully manage the growing complexity of systems where conventional engineering and scientific methodologies and technologies based on learning and adaptability come to their limits and new ways are nowadays required. The transition from adaptable to evolvable and finally to self-evolvable systems is highlighted, self-properties such as self-organization, self-configuration, and self-repairing are introduced and challenges and limitations of the self-evolvable engineering systems are evaluated.

The purpose of this conference is to bring together leading researchers from the evolvable hardware community, representatives of the automated design and programmable/reconfigurable hardware communities, technology developers and end-users from the aerospace, military and commercial sectors. The focus of EH 2002 is evolvable hardware for safer systems.

A fascinating look into nurturing and parenting in the natural world, supplemented with original illustrations For readers of Becoming Animal and World of Wonders A beautiful resource for Nature advocates, parents-to-be, Animal lovers, and anyone who seeks to restore wellbeing on our planet, The Evolved Nest reconnects us to lessons from the Animal world and shows us how to restore wellness in our families, communities, and lives. Each of 10 chapters explores a different animal’s parenting model, sharing species-specific adaptations that allow each to thrive in their “evolved nests.” You’ll learn: How Wolves build an internal moral compass How Beavers foster a spirit of play in their children How Octopuses develop emotional and social intelligence How, when, and whether (or not) Brown Bears decide to have children What their lessons can teach you--whether you’re a parent, grandparent, caregiver, or childfree Psychologists Drs. Darcia Narvaez and Gay Bradshaw show us how each evolved nest offers inspiration for reexamining our own systems of nurturing, understanding, and caring for our young and each other. Alongside beautiful illustrations, stunning scientific facts, and lessons in neuroscience, psychology, and evolutionary biology, we learn to care deeper: to restore our innate place within the natural world and fight for an ecology of life that supports our flourishing in balance with Nature alongside our human and non-human family.

This invaluable book comprehensively describes evolutionary robotics and computational intelligence, and how different computational intelligence techniques are applied to robotic system design. It embraces the most widely used evolutionary approaches with their merits and drawbacks, presents some related experiments for robotic behavior evolution and the results achieved, and shows promising future research directions. Clarity of explanation is emphasized such that a modest knowledge of basic evolutionary computation, digital circuits and engineering design will suffice for a thorough understanding of the material. The book is ideally suited to computer scientists, practitioners and researchers keen on computational intelligence techniques, especially the evolutionary algorithms in autonomous robotics at both the hardware and software levels. Sample Chapter(s). Chapter 1: Artificial Evolution Based Autonomous Robot Navigation (184 KB). Contents: Artificial Evolution Based Autonomous Robot Navigation; Evolvable Hardware in Evolutionary Robotics; FPGA-Based Autonomous Robot Navigation via Intrinsic Evolution; Intelligent Sensor Fusion and Learning for Autonomous Robot Navigation; Task-Oriented Developmental Learning for Humanoid Robots; Bipedal Walking Through Reinforcement Learning; Swing Time Generation for Bipedal Walking Control Using GA Tuned Fuzzy Logic Controller; Bipedal Walking: Stance Ankle Behavior Optimization Using Genetic Algorithm. Readership: Researchers in evolutionary robotics, and graduate and advanced undergraduate students in computational intelligence.

Philosophical Foundations of Evolutionary Psychology describes the unique relationship between early schools of thought in Greek philosophy, modern psychology, and most recently evolutionary psychology. This volume provides the reader with a concise history and description of some of the most important theories used in understanding human behaviors (i.e., the mind-body duality, the essence of human nature, and how humans have evolved to cooperate with each other) and how the physical characteristics of communities have contributed to positive (i.e., prosocial) or destructive (i.e., antisocial) behavior. It explores human nature from the philosophical perspectives of Socrates, Plato, Descartes, Locke, and Rousseau as contributing factors to the development of modern psychology (i.e., Structuralism, Functionalism, Behaviorism, and Biopsychology) that ultimately is combined with evolutionary psychology. Philosophical Foundations of Evolutionary Psychology alsoincorporates various topics of psychology that support the development of evolutionary psychology such as language and communication, gender differences, aggression, cooperative behaviors, and natural selection.

Nature-Inspired Algorithms have been gaining much popularity in recent years due to the fact that many real-world optimisation problems have become increasingly large, complex and dynamic. The size and complexity of the problems nowadays require the development of methods and solutions whose efficiency is measured by their ability to find acceptable results within a reasonable amount of time, rather than an ability to guarantee the optimal solution. This volume 'Nature-Inspired Algorithms for Optimisation' is a collection of the latest state-of-the-art algorithms and important studies for tackling various kinds of optimisation problems. It comprises 18 chapters, including two introductory chapters which address the fundamental issues that have made optimisation problems difficult to solve and explain the rationale for seeking inspiration from nature. The contributions stand out through their novelty and clarity of the algorithmic descriptions and analyses, and lead the way to interesting and varied new applications.

This book reports on innovative concepts and practical solutions at the intersection between engineering design, engineering production and industrial management. It covers cutting-edge design, modeling and control of dynamic and multiphysics systems, knowledge management systems in industry 4.0, cyber-physical production systems, additive and sustainable manufacturing and many other related topics. The original, carefully selected, peer-reviewed chapters highlight collaborative works between different countries and between industry and universities, thus offering a timely snapshot for the research and industrial communities alike, as well as a bridge to facilitate communication and collaboration.