"So far, EA implementation of military space programs has produced mixed results. The capabilities and requirements definition and management processes are major challenges in all EA programs. EA programs require an evolutionary costing approach; most cost analysts interviewed expressed generally positive views about EA."--BOOK JACKET.

The Department of Defense (DoD) recently adopted evolutionary acquisition, a dynamic strategy for the development and acquisition of its defense systems. Evolutionary defense systems are planned, in advance, to be developed through several stages in a single procurement program. Each stage is planned to produce a viable system which could be fielded. The system requirements for each stage of development may be specified in advance of a given stage or may be decided at the outset of that stage's development. Due to the different stages that comprise an evolutionary system, there exists a need for careful reexamination of current testing and evaluation policies and processes, which were designed for single-stage developments. The Office of the Under Secretary of Defense for Acquisition, Technology and Logistics (USD-AT&L) and the Director of Operational Testing and Evaluation (DOT&E) asked the Committee on National Statistics (CNSTAT) of the National Academies to examine the key issues and implications for defense testing from the introduction of evolutionary acquisition. The CNSTAT was charged with planning and conducting a workshop to study test strategies for the evolutionary acquisition. The committee reviewed defense materials defining evolutionary acquisition and interviewed test officials from the three major test service agencies to understand the current approaches used in testing systems procured through evolutionary acquisition. The committee also examined possible alternatives to identify problems in implementation. At the workshop that took place on December 13-14, 2004, the committee tried to answer many questions including: What are the appropriate roles and objectives for testing in an evolutionary environment?, Can a systematic, disciplined process be developed for testing and evaluation in such a fluid and flexible environment?, and Is there adequate technical expertise within the acquisition community to fully exploit data gathered from previous stages to effectively combine information from various sources for test design and analysis?. Testing of Defense Systems in an Evolutionary Acquisition Environment provides the conclusions and recommendations of the CNSTAT following the workshop and its other investigations.

A work that reveals the profound links between the evolution, acquisition, and processing of language, and proposes a new integrative framework for the language sciences. Language is a hallmark of the human species; the flexibility and unbounded expressivity of our linguistic abilities is unique in the biological world. In this book, Morten Christiansen and Nick Chater argue that to understand this astonishing phenomenon, we must consider how language is created: moment by moment, in the generation and understanding of individual utterances; year by year, as new language learners acquire language skills; and generation by generation, as languages change, split, and fuse through the processes of cultural evolution. Christiansen and Chater propose a revolutionary new framework for understanding the evolution, acquisition, and processing of language, offering an integrated theory of how language creation is intertwined across these multiple timescales. Christiansen and Chater argue that mainstream generative approaches to language do not provide compelling accounts of language evolution, acquisition, and processing. Their own account draws on important developments from across the language sciences, including statistical natural language processing, learnability theory, computational modeling, and psycholinguistic experiments with children and adults. Christiansen and Chater also consider some of the major implications of their theoretical approach for our understanding of how language works, offering alternative accounts of specific aspects of language, including the structure of the vocabulary, the importance of experience in language processing, and the nature of recursive linguistic structure.

"Traditionally, studies and textbooks in Neurology or Psychiatry, as well as allied disciplines, deal with proximate causes of diseases and therapies, but remain mute or minimally interested in their ultimate causes including the phylogeny and adaptive significance of disease manifestations. Yet, as clinicians or basic researchers, we are conscious of potential evolutionary roots of neurological and psychiatric symptoms, often offering a rudimentary explanation but never delving deeply into the current role of evolutionary science as it relates to health and disease. We may miss appreciation of the role of adaptive properties, evolutionarily based neuronal circuitries, unbalanced cellular energy demands, and the potential health consequences of residual syndromic behaviors that were possibly useful in early times of human development, but presently are obsolete and pathological. The problem is amplified, because there is often no interdisciplinary dialogue between anthropology and evolutionary biology on one side and clinical sciences on the other side. However, the evolutionary tracing back of disease pathways may disclose unexpected insights and trigger the design of innovative research as well as propel the development of new therapeutic interventions. There could also be a better apprehension of compensatory behaviors, both at the cellular level as well as the systemic the behavioural levels, that could be the expected fruits of such collaborations. So far scientists fall short in modeling the complexity of human (social) life, human language, or manual dexterity, and mental or emotional behaviors that typify human neurological or psychological function and dysfunction. Finally, there remain obstacles in the form of poor animal modeling for human brain diseases and for human longevity. The present book aims to fill these gaps by presenting an evolutionary view of neurological and psychiatric conditions that is meant to complement and enrich existing medical perspectives"--

Why do people resort to plastic surgery to look young? Why are stepchildren at greatest risk of fatal abuse? Why do we prefer gossip to algebra? Why must Dogon wives live alone in a dark hut for five days a month? Why are young children good at learning language but not sharing? Over the past decade, psychologists and behavioral ecologists have been finding answers to such seemingly unrelated questions by applying an evolutionary perspective to the study of human behavior and psychology. Human Evolutionary Psychology is a comprehensive, balanced, and readable introduction to this burgeoning field. It combines a sophisticated understanding of the basics of evolutionary theory with a solid grasp of empirical case studies. Covering not only such traditional subjects as kin selection and mate choice, this text also examines more complex understandings of marriage practices and inheritance rules and the way in which individual action influences the structure of societies and aspects of cultural evolution. It critically assesses the value of evolutionary explanations to humans in both modern Western society and traditional preindustrial societies. And it fairly presents debates within the field, identifying areas of compatibility among sometimes competing approaches. Combining a broad scope with the more in-depth knowledge and sophisticated understanding needed to approach the primary literature, this text is the ideal introduction to the exciting and rapidly expanding study of human evolutionary psychology.

Researchers and practitioners alike are increasingly turning to search, op timization, and machine-learning procedures based on natural selection and natural genetics to solve problems across the spectrum of human endeavor. These genetic algorithms and techniques of evolutionary computation are solv ing problems and inventing new hardware and software that rival human designs. The Kluwer Series on Genetic Algorithms and Evolutionary Computation pub lishes research monographs, edited collections, and graduate-level texts in this rapidly growing field. Primary areas of coverage include the theory, implemen tation, and application of genetic algorithms (GAs), evolution strategies (ESs), evolutionary programming (EP), learning classifier systems (LCSs) and other variants of genetic and evolutionary computation (GEC). The series also pub lishes texts in related fields such as artificial life, adaptive behavior, artificial immune systems, agent-based systems, neural computing, fuzzy systems, and quantum computing as long as GEC techniques are part of or inspiration for the system being described. This encyclopedic volume on the use of the algorithms of genetic and evolu tionary computation for the solution of multi-objective problems is a landmark addition to the literature that comes just in the nick of time. Multi-objective evolutionary algorithms (MOEAs) are receiving increasing and unprecedented attention. Researchers and practitioners are finding an irresistible match be tween the popUlation available in most genetic and evolutionary algorithms and the need in multi-objective problems to approximate the Pareto trade-off curve or surface.