Darwin's greatest accomplishment was to show how life might be explained as the result of natural selection. But does Darwin's theory mean that life was unintended? William A. Dembski argues that it does not. As the leading proponent of intelligent design, Dembski reveals a designer capable of originating the complexity and specificity found throughout the cosmos. Scientists and theologians alike will find this book of interest as it brings the question of creation firmly into the realm of scientific debate. The paperback is updated with a new Preface by the author.

“Everyone who is successful, regardless of age, race, or ethnicity, at some point in their lives received an opportunity. Someone believed in them enough to give them a chance.”These are the words of Rodney Carroll, one of America’s most innovative minds and a leading architect of the welfare to work movement. They encapsulate his inspiring memoir,No Free Lunch, the story of a man who rose to the top–and returned to bring millions of people along with him. Raised in an area both economically and emotionally depressed, Rodney and his siblings were forced onto welfare after Rodney’s alcoholic and abusive mother was declared unfit to raise her children. Though lured by gangs that aimed to “draft” him into their midst, he clung instead to his wise and loving grandmother and his innate desire to “make a difference.” A part-time job as a truck loader for UPS would change Rodney’s life forever–and eventually change the lives of others who were looking for a chance to work. By improving the efficiency of others at UPS, Rodney was rewarded with promotions. By balancing his successes and setbacks, applauding others’ accomplishments, and disciplining not humiliating, he learned how to manage men and women, lead departments, and, at last, to lift up others who started out as humbly as he had. Putting his own job on the line, Rodney created a program to employ welfare recipients at UPS–a plan that would become a model for others across the country. Initially derided by others as “those people,” these new workers responded to Rodney’s faith in them, and their new self-esteem led to new self-sufficiency. Written with vigor and humor,No Free Lunchis a testament to one man’s tenacity and compassion, a sweeping story that starts in a slum and ends on a stage shared with President Clinton, a stirring book about one American’s fight for the independence of millions.

This book reviews the state-of-the-art developments in nature-inspired algorithms and their applications in various disciplines, ranging from feature selection and engineering design optimization to scheduling and vehicle routing. It introduces each algorithm and its implementation with case studies as well as extensive literature reviews, and also includes self-contained chapters featuring theoretical analyses, such as convergence analysis and no-free-lunch theorems so as to provide insights into the current nature-inspired optimization algorithms. Topics include ant colony optimization, the bat algorithm, B-spline curve fitting, cuckoo search, feature selection, economic load dispatch, the firefly algorithm, the flower pollination algorithm, knapsack problem, octonian and quaternion representations, particle swarm optimization, scheduling, wireless networks, vehicle routing with time windows, and maximally different alternatives. This timely book serves as a practical guide and reference resource for students, researchers and professionals.

Metaheuristics, and evolutionary algorithms in particular, are known to provide efficient, adaptable solutions for many real-world problems, but the often informal way in which they are defined and applied has led to misconceptions, and even successful applications are sometimes the outcome of trial and error. Ideally, theoretical studies should explain when and why metaheuristics work, but the challenge is huge: mathematical analysis requires significant effort even for simple scenarios and real-life problems are usually quite complex. In this book the editors establish a bridge between theory and practice, presenting principled methods that incorporate problem knowledge in evolutionary algorithms and other metaheuristics. The book consists of 11 chapters dealing with the following topics: theoretical results that show what is not possible, an assessment of unsuccessful lines of empirical research; methods for rigorously defining the appropriate scope of problems while acknowledging the compromise between the class of problems to which a search algorithm is applied and its overall expected performance; the top-down principled design of search algorithms, in particular showing that it is possible to design algorithms that are provably good for some rigorously defined classes; and, finally, principled practice, that is reasoned and systematic approaches to setting up experiments, metaheuristic adaptation to specific problems, and setting parameters. With contributions by some of the leading researchers in this domain, this book will be of significant value to scientists, practitioners, and graduate students in the areas of evolutionary computing, metaheuristics, and computational intelligence.

Small-scale agricultural producers in the peripheral world are often condescendingly assumed to be a single social class (‘the peasantry’) to be pitted against the state or corporation. This book challenges this rather idealistic view by demonstrating that under current capitalist social relations (competition, efficiency and productivity, and profit maximisation), these agricultural producers have been differentiated into different agrarian classes by exploitation. By comparing two different contexts of local agrarian change in Indonesia—rice cultivation in Java and oil palm in Sumatra—this book exposes the different class locations of the agrarian classes among petty agricultural producers and the class relations between them. These are often inextricably linked to gender, clanship and generational issues. The power of class dynamics crucially shapes how agricultural production in both rice and oil palm is organised. The share received by different agrarian classes from the production site then prominently shapes the different nature of class reproduction for each agrarian class. This analysis demonstrates that the different agrarian classes possess different capacities and responses in their relation to the state or corporations. Any real emancipation attempt in the Indonesian countryside (and beyond) must start from a proper understanding of these class dynamics. This book marks a significant contribution to the literature on agrarian change, the political economy of development, rural development and Marxist political economy.

Software testing is traditionally seen as a difficult and time consuming activity that is hard to embed in the software development process. This book provides a different view. It explains to stakeholders how testing can add value to software development and doing business, and provides the tester with practical information. TestGoal is not just another methodology. Several good testing methodologies exist. But, like any other profession, also testing encompasses more than the simple application of a methodology. After all, strict adherence to a specific methodology is no guarantee for success. Success stems from the mindset, enthusiasm, knowledge and skill of the tester. These factors determine whether a methodology is applied successfully and whether testing takes on a result-driven character. And that’s what TestGoal is about: a result-driven attitude, testing principles and expertise as fundament, and a hands-on six step plan to enable result driven testing. Derk-Jan de Grood and his colleagues from Collis, an international software testing company, know about the main pitfalls in test projects from their extensive professional experience. TestGoal has emerged from the office floor and captures over a decade of best practice. TestGoal is made by professionals for professionals, and it combines the mindset, knowledge, and skills required to add value with testing and make software development more successful. This book explains in a clear language how you can make testing result-driven. It explains why testing is important and describes all of the activities involved in testing. It is enriched with recognizable examples, practical tips and useful checklists. This makes it a "GO kit" that enables testers to immediately get started and add value to their organization.

This book examines the mismatch between discrete programs, which lie at the center of modern applied mathematics, and the continuous space phenomena they simulate. The author considers whether we can imagine continuous spaces of programs, and asks what the structure of such spaces would be and how they would be constituted. He proposes a functional analysis of program spaces focused through the lens of iterative optimization. The author begins with the observation that optimization methods such as Genetic Algorithms, Evolution Strategies, and Particle Swarm Optimization can be analyzed as Estimation of Distributions Algorithms (EDAs) in that they can be formulated as conditional probability distributions. The probabilities themselves are mathematical objects that can be compared and operated on, and thus many methods in Evolutionary Computation can be placed in a shared vector space and analyzed using techniques of functional analysis. The core ideas of this book expand from that concept, eventually incorporating all iterative stochastic search methods, including gradient-based methods. Inspired by work on Randomized Search Heuristics, the author covers all iterative optimization methods and not just evolutionary methods. The No Free Lunch Theorem is viewed as a useful introduction to the broader field of analysis that comes from developing a shared mathematical space for optimization algorithms. The author brings in intuitions from several branches of mathematics such as topology, probability theory, and stochastic processes and provides substantial background material to make the work as self-contained as possible. The book will be valuable for researchers in the areas of global optimization, machine learning, evolutionary theory, and control theory.