All living things are remarkably complex, yet their DNA is unstable, undergoing countless random mutations over generations. Despite this instability, most animals do not grow two heads or die, plants continue to thrive, and bacteria continue to divide. Robustness and Evolvability in Living Systems tackles this perplexing paradox. The book explores why genetic changes do not cause organisms to fail catastrophically and how evolution shapes organisms' robustness. Andreas Wagner looks at this problem from the ground up, starting with the alphabet of DNA, the genetic code, RNA, and protein molecules, moving on to genetic networks and embryonic development, and working his way up to whole organisms. He then develops an evolutionary explanation for robustness. Wagner shows how evolution by natural selection preferentially finds and favors robust solutions to the problems organisms face in surviving and reproducing. Such robustness, he argues, also enhances the potential for future evolutionary innovation. Wagner also argues that robustness has less to do with organisms having plenty of spare parts (the redundancy theory that has been popular) and more to do with the reality that mutations can change organisms in ways that do not substantively affect their fitness. Unparalleled in its field, this book offers the most detailed analysis available of all facets of robustness within organisms. It will appeal not only to biologists but also to engineers interested in the design of robust systems and to social scientists concerned with robustness in human communities and populations.

Essays on evolvability from the perspectives of quantitative and population genetics, evolutionary developmental biology, systems biology, macroevolution, and the philosophy of science. Evolvability—the capability of organisms to evolve—wasn’t recognized as a fundamental concept in evolutionary theory until 1990. Though there is still some debate as to whether it represents a truly new concept, the essays in this volume emphasize its value in enabling new research programs and facilitating communication among the major disciplines in evolutionary biology. The contributors, many of whom were instrumental in the development of the concept of evolvability, synthesize what we have learned about it over the past thirty years. They focus on the historical and philosophical contexts that influenced the emergence of the concept and suggest ways to develop a common language and theory to drive further evolvability research. The essays, drawn from a workshop on evolvability hosted in 2019–2020 by the Center of Advanced Study at the Norwegian Academy of Science and Letters, in Oslo, provide scientific and historical background on evolvability. The contributors represent different disciplines of evolutionary biology, including quantitative and population genetics, evolutionary developmental biology, systems biology and macroevolution, as well as the philosophy of science. This pl[urality of approaches allows researchers in disciplines as diverse as developmental biology, molecular biology, and systems biology to communicate with those working in mainstream evolutionary biology. The contributors also discuss key questions at the forefront of research on evolvability. Contributors: J. David Aponte, W. Scott Armbruster, Geir H. Bolstad, Salomé Bourg, Ingo Brigandt, Anne Calof, James M. Cheverud, Josselin Clo, Frietson Galis, Mark Grabowski, Rebecca Green, Benedikt Hallgrímsson, Thomas F. Hansen, Agnes Holstad, David Houle, David Jablonski, Arthur Lander, Arnaud LeRouzic, Alan C. Love, Ralph Marcucio, Michael B. Morrissey, Laura Nuño de la Rosa, Øystein H. Opedal, Mihaela Pavličev, Christophe Pélabon, Jane M. Reid, Heather Richbourg, Jacqueline L. Sztepanacz, Masahito Tsuboi, Cristina Villegas, Marta Vidal-García, Kjetil L. Voje, Andreas Wagner, Günter P. Wagner, Nathan M. Young

Embodied and evolving systems — biological or robotic — are interacting networks of structure, function, information, and behavior. Understanding these complex systems is the goal of the research presented in this book. We address different questions and hypotheses about four essential topics in complex systems: evolvability, environments, embodiment, and emergence. Using a variety of approaches, we provide different perspectives on an overarching, unifying question: How can embodied and evolutionary robotics illuminate (1) principles underlying biological evolving systems and (2) general analytical frameworks for studying embodied evolving systems? The answer — model biological processes to operate, develop, and evolve situated, embodied robots.

Evolvability, the ability to respond effectively to change, represents a major challenge to today's high-end embedded systems, such as those developed in the medical domain by Philips Healthcare. These systems are typically developed by multi-disciplinary teams, located around the world, and are in constant need of upgrading to provide new advanced features, to deal with obsolescence, and to exploit emerging enabling technologies. Despite the importance of evolvability for these types of systems, the field has received scant attention from the scientific and engineering communities. Views on Evolvability of Embedded Systems focuses on the topic of evolvability of embedded systems from an applied scientific perspective. In particular, the book describes results from the Darwin project that researched evolvability in the context of Magnetic Resonance Imaging (MRI) systems. This project applied the Industry-as-Laboratory paradigm, in which industry and academia join forces to ensure continuous knowledge and technology transfer during the project’s lifetime. The Darwin project was a collaboration between the Embedded Systems Institute, the MRI business unit of Philips Healthcare, Philips Research, and five Dutch universities. Evolvability was addressed from a system engineering perspective by a number of researchers from different disciplines such as software-, electrical- and mechanical engineering, with a clear focus on economic decision making. The research focused on four areas: data mining, reference architectures, mechanisms and patterns for evolvability, in particular visualization & modelling, and economic decision making. Views on Evolvability of Embedded Systems is targeted at both researchers and practitioners; they will not only find a state-of-the-art overview on evolvability research, but also guidelines to make systems more evolvable and new industrially-validated techniques to improve the evolvability of embedded systems.

Modularity in Development and Evolution offers the first sustained exploration of modules from developmental and evolutionary perspectives. Contributors discuss what modularity is, how it can be identified and modeled, how it originated and evolved, and its biological significance. Covering modules at levels ranging from genes to colonies, the book focuses on their roles not just in structures but also in processes such as gene regulation. Among many exciting findings, the contributors demonstrate how modules can highlight key constraints on evolutionary processes. A timely synthesis of a crucial topic, Modularity in Development and Evolution shows the invaluable insights modules can give into both developmental complexities and their evolutionary origins.

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.

Adopting a groundbreaking approach, the highly regarded author shows how to design methods for planning increasingly complex experiments. He begins with a brief introduction to standard quality methods and the technology in standard electric circuits. The book then gives numerous examples of how to apply the proposed methodology in a series of real-life case studies. Although these case studies are taken from the printed circuit board industry, the methods are equally applicable to other fields of engineering.