In the 150 years since Darwin, evolutionary biology has proven as essential as it is controversial, a critical concept for answering questions about everything from the genetic code and the structure of cells to the reproduction, development, and migration of animal and plant life. But today, as David P. Mindell makes undeniably clear in The Evolving World, evolutionary biology is much more than an explanatory concept. It is indispensable to the world we live in. This book provides the first truly accessible and balanced account of how evolution has become a tool with applications that are thoroughly integrated, and deeply useful, in our everyday lives and our societies, often in ways that we do not realize. When we domesticate wild species for agriculture or companionship; when we manage our exposure to pathogens and prevent or control epidemics; when we foster the diversity of species and safeguard the functioning of ecosystems: in each of these cases, Mindell shows us, evolutionary biology applies. It is at work when we recognize that humans represent a single evolutionary family with variant cultures but shared biological capabilities and motivations. And last but not least, we see here how evolutionary biology comes into play when we use knowledge of evolution to pursue justice within the legal system and to promote further scientific discovery through education and academic research. More than revealing evolution's everyday uses and value, The Evolving World demonstrates the excitement inherent in its applications--and convinces us as never before that evolutionary biology has become absolutely necessary for human existence.

A new account of the central role developmental processes play in evolution A new scientific view of evolution is emerging—one that challenges and expands our understanding of how evolution works. Recent research demonstrates that organisms differ greatly in how effective they are at evolving. Whether and how each organism adapts and diversifies depends critically on the mechanistic details of how that organism operates—its development, physiology, and behavior. That is because the evolutionary process itself has evolved over time, and continues to evolve. The scientific understanding of evolution is evolving too, with groundbreaking new ways of explaining evolutionary change. In this book, a group of leading biologists draw on the latest findings in evolutionary genetics and evo-devo, as well as novel insights from studies of epigenetics, symbiosis, and inheritance, to examine the central role that developmental processes play in evolution. Written in an accessible style, and illustrated with fascinating examples of natural history, the book presents recent scientific discoveries that expand evolutionary biology beyond the classical view of gene transmission guided by natural selection. Without undermining the central importance of natural selection and other Darwinian foundations, new developmental insights indicate that all organisms possess their own characteristic sets of evolutionary mechanisms. The authors argue that a consideration of developmental phenomena is needed for evolutionary biologists to generate better explanations for adaptation and biodiversity. This book provides a new vision of adaptive evolution.

Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language provides the first comprehensive introduction to Grammatical Evolution, a novel approach to Genetic Programming that adopts principles from molecular biology in a simple and useful manner, coupled with the use of grammars to specify legal structures in a search. Grammatical Evolution's rich modularity gives a unique flexibility, making it possible to use alternative search strategies - whether evolutionary, deterministic or some other approach - and to even radically change its behavior by merely changing the grammar supplied. This approach to Genetic Programming represents a powerful new weapon in the Machine Learning toolkit that can be applied to a diverse set of problem domains.

This book provides a collection of fourty articles containing new material on both theoretical aspects of Evolutionary Computing (EC), and demonstrating the usefulness/success of it for various kinds of large-scale real world problems. Around 23 articles deal with various theoretical aspects of EC and 17 articles demonstrate the success of EC methodologies. These articles are written by leading experts of the field from different countries all over the world.

This book presents several recent advances on Evolutionary Computation, specially evolution-based optimization methods and hybrid algorithms for several applications, from optimization and learning to pattern recognition and bioinformatics. This book also presents new algorithms based on several analogies and metafores, where one of them is based on philosophy, specifically on the philosophy of praxis and dialectics. In this book it is also presented interesting applications on bioinformatics, specially the use of particle swarms to discover gene expression patterns in DNA microarrays. Therefore, this book features representative work on the field of evolutionary computation and applied sciences. The intended audience is graduate, undergraduate, researchers, and anyone who wishes to become familiar with the latest research work on this field.

This book constitutes the refereed proceedings of the International Conference on the Applications of Evolutionary Computation, EvoApplications 2011, held in Torino, Italy, in April 2011 colocated with the Evo* 2011 events. Thanks to the large number of submissions received, the proceedings for EvoApplications 2011 are divided across two volumes (LNCS 6624 and 6625). The present volume contains contributions for EvoCOMNET, EvoFIN, EvoIHOT, EvoMUSART, EvoSTIM, and EvoTRANSLOC. The 51 revised full papers presented were carefully reviewed and selected from numerous submissions. This volume presents an overview about the latest research in EC. Areas where evolutionary computation techniques have been applied range from telecommunication networks to complex systems, finance and economics, games, image analysis, evolutionary music and art, parameter optimization, scheduling, and logistics. These papers may provide guidelines to help new researchers tackling their own problem using EC.