Stories of True Crime in Tudor and Stuart England is an original collection of thirty stories of true crime during the period 1580-1700. Published in short books known as chapbooks, these stories proliferated in early modern popular literature. The chapbooks included in this collection describe serious, horrifying and often deeply personal stories of murder and attempted murder, infanticide, suicide, rape, arson, highway robbery, petty treason and witchcraft. These criminal cases reveal the fascinating complexities of early modern English society. The vivid depictions of these stories were used by the English church and state to describe the proper boundaries of behaviour, and the dangers that could result from the sins of avarice, apathy, vice or violence. Readers will learn about the public interest and involvement in crime and punishment and the way the criminal justice system was used to correct and deter criminal activity and restore social boundaries such as rank, gender, family, religion, and physical boundaries of person and property. Perfect for the student reader, this collection provides guided access to these exciting sources. Each transcription is modernized and annotated and is preceded by a brief discussion of key historical context and themes. Including an introductory essay on the topic of the English criminal justice system in the early modern period, as well as a glossary of key terms in English criminal law, this is an ideal introduction for students of crime and criminal justice in England.

This book discusses a class of algorithms which rely on analogies to natural processes - algorithms based on the principle of evolution, i.e., survival of the fittest. In these algorithms, called evolution programs, a population of individuals undergo a sequence of transformations. The individuals strive for survival: a selection scheme biased towards fitter individuals selects the next generation. After some generations, the program converges and the best individual hopefully represents the optimum solution. Hence evolution programming techniques are applicable to various hard optimization problems. The book discusses constrained optimization problems in the areas of optimal control, operations research, and engineering. The problems include optimization of functions with linear constraints, the traveling salesman problem, scheduling and partitioning problems, etc. All methods are illustrated by results obtained from various experimental systems. The book collects, in a unified and comprehensive manner, the results of evolution programming techniques previously available only in widely scattered research papers. The importance of these techniques has been growing in the last decade, since evolution programs are parallel in nature, and parallelism is one of the most promising directions in computer science. The book is self-contained and the only prerequisite is basic undergraduate mathematics. It is aimed at researchers, practitioners, and graduate students in the areas of computer science (especially artificial intelligence), operations research, and engineering.

This book discusses a class of algorithms which rely on analogies to natural processes - algorithms based on the principle of evolution, i.e., survival of the fittest. In these algorithms, called evolution programs, a population of individuals undergo a sequence of transformations. The individuals strive for survival: a selection scheme biased towards fitter individuals selects the next generation. After some generations, the program converges and the best individual hopefully represents the optimum solution. Hence evolution programming techniques are applicable to various hard optimization problems. The book discusses constrained optimization problems in the areas of optimal control, operations research, and engineering. The problems include optimization of functions with linear constraints, the traveling salesman problem, scheduling and partitioning problems, etc. All methods are illustrated by results obtained from various experimental systems. The book collects, in a unified and comprehensive manner, the results of evolution programming techniques previously available only in widely scattered research papers. The importance of these techniques has been growing in the last decade, since evolution programs are parallel in nature, and parallelism is one of the most promising directions in computer science. The book is self-contained and the only prerequisite is basic undergraduate mathematics. It is aimed at researchers, practitioners, and graduate students in the areas of computer science (especially artificial intelligence), operations research, and engineering.

The solving of multi-objective problems (MOPs) has been a continuing effort by humans in many diverse areas, including computer science, engineering, economics, finance, industry, physics, chemistry, and ecology, among others. Many powerful and deterministic and stochastic techniques for solving these large dimensional optimization problems have risen out of operations research, decision science, engineering, computer science and other related disciplines. The explosion in computing power continues to arouse extraordinary interest in stochastic search algorithms that require high computational speed and very large memories. A generic stochastic approach is that of evolutionary algorithms (EA). Such algorithms have been demonstrated to be very powerful and generally applicable for solving different single objective problems. Their fundamental algorithmic structures can also be applied to solving many multi-objective problems. In this book, the various features of multi-objective evolutionary algorithms (MOEAs) are presented in an innovative and unique fashion, with detailed customized forms suggested for a variety of applications. Also, extensive MOEA discussion questions and possible research directions are presented at the end of each chapter. For additional information and supplementary teaching materials, please visit the authors' website at http://www.cs.cinvestav.mx/~EVOCINV/bookinfo.html.

Product Description: Artificial neural networks, genetic algorithms and the ant colony optimization algorithm have become a highly effective tool for solving hard optimization problems. As their popularity has increased, applications of these algorithms have grown in more than equal measure...read more

Product Description: This book presents original research on fuzzy inference, describes a new model for solving inverse problems of fuzzy inference and presents applications in system control problems, sport forecasting, automobile design, system reliability analysis and more.

Product Description: Since the introduction of genetic algorithms in the 1970s, an enormous number of articles together with several significant monographs and books have been published on this methodology. As a result, genetic algorithms have made a major contribution to optimization, adaptation, and learning in a wide variety of unexpected fields...read more

Product Description: The study of the genetic basis for evolution has flourished in this century, as well as our understanding of the evolvability and programmability of biological systems. Genetic algorithms meanwhile grew out of the realization that a computer program could use the biologically-inspired processes of mutation, recombination, and selection to solve hard optimization problems...read more

Product Description: This IMA Volume in Mathematics and its Applications EVOLUTIONARY ALGORITHMS is based on the proceedings of a workshop that was an integral part of the 1996-97 IMA program on "MATHEMATICS IN HIGH-PERFORMANCE COMPUTING." I thank Lawrence David Davis (Tica Associates), Kenneth De Jong (Computer Science, George Mason University), Michael D...read more

Product Description: The optimization of optical systems is a very old problem. As soon as lens designers discovered the possibility of designing optical systems, the desire to improve those systems by the means of optimization began. For a long time the optimization of optical systems was connected with well-known mathematical theories of optimization which gave good results, but required lens designers to have a strong knowledge about optimized optical systems...read more

Product Description: Evolutionary Algorithms for Embedded System Design describes how Evolutionary Algorithm (EA) concepts can be applied to circuit and system design - an area where time-to-market demands are critical. EAs create an interesting alternative to other approaches since they can be scaled with the problem size and can be easily run on parallel computer systems...read more

Product Description: OmeGA: A Competent Genetic Algorithm for Solving Permutation and Scheduling Problems addresses two increasingly important areas in GA implementation and practice. OmeGA, or the ordering messy genetic algorithm, combines some of the latest in competent GA technology to solve scheduling and other permutation problems...read more

Product Description: The field of optimization is interdisciplinary in nature, and has been making a significant impact on many disciplines. As a result, it is an indispensable tool for many practitioners in various fields. Conventional optimization techniques have been well established and widely published in many excellent textbooks...read more

Product Description: Describes how evolutionary algorithms (EAs) can be used to identify, model, and minimize day-to-day problems that arise for researchers in optimization and mobile networking Mobile ad hoc networks (MANETs), vehicular networks (VANETs), sensor networks (SNs), and hybrid networks—each of these require a designer’s keen sense and knowledge of evolutionary algorithms in order to help with the common issues that plague professionals involved in optimization and mobile networking...read more

Product Description: The fact that I have the opportunity to present a second edition of this monograph is an indicator for the growing size of the community concerned with agent-based computational economics. The rapid developments in this field make it very difficult to keep a volume like this, which is partly devoted to surveying the literature, up to date...read more

Product Description: The articles presented here were selected from preliminary versions presented at the International Conference on Genetic Algorithms in June 1991, as well as at a special Workshop on Genetic Algorithms for Machine Learning at the same Conference...read more