Zbigniew Michalewicz – författare

Few terms have captured our imagination in recent times like "Artificial Intelligence," and it now seems that everyone "know" about AI; that everyone has an opinion. And yet, few people actually understand how the technology can be harnessed to generate commercial outcomes.

Written for the modern-day business manager, this book examines Artificial Intelligence from the perspective of decision-making, because the quality of the decisions we make defines the quality of the future we create for ourselves and our organizations. In the same way that calculators have improved our ability to make better decisions-followed by spreadsheets, reporting tools, and countless other software applications-Artificial Intelligence is fast becoming the latest "calculator" to assist us, and one that happens to be particularly well-suited for the speed, noise, and complexity of the modern world ...

Internationally renowned new technologies expert, Dr Zbigniew Michalewicz has published over 200 articles and 15 books on the subjects of business intelligence, predictive data mining, and optimisation. Leonardo Arantes is a dynamic sales and marketing professional, with a reputation for using creative problem-solving to take products to market and deliver on customer needs. Matt Michalewicz has more than 20 years of experience in starting and running high-growth tech companies, especially in the areas of machine learning, predictive analytics, and decision optimisation.

In the modern information era, managers must recognize the competitive opportunities represented by decision-support tools. Adaptive business intelligence systems combine prediction and optimization techniques to assist decision makers in complex, rapidly changing environments. These systems address the fundamental questions: What is likely to happen in the future? And what is the best decision right now? Adaptive Business Intelligence includes elements of data mining, predictive modeling, forecasting, optimization, and adaptability.

The authors have considerable academic research backgrounds in artificial intelligence and related fields, combined with years of practical consulting experience in businesses and industries worldwide. In this book they explain the science and application of numerous prediction and optimization techniques, as well as how these concepts can be used to develop adaptive systems. The techniques covered include linear regression, time-series forecasting, decision trees and tables, artificial neural networks, genetic programming, fuzzy systems, genetic algorithms, simulated annealing, tabu search, ant systems, and agent-based modeling.

This book is suitable for business and IT managers who make decisions in complex industrial and service environments, nonspecialists who want to understand the science behind better predictions and decisions, and students and researchers who need a quick introduction to this field.

Many advances have been made recently in metaheuristic methods, from theory to applications. The editors, both leading experts in this field, have assembled a team of researchers to contribute 21 chapters organized into parts on simulated annealing, tabu search, ant colony algorithms, general-purpose studies of evolutionary algorithms, applications of evolutionary algorithms, and various metaheuristics.

The book gathers contributions related to the following topics: theoretical developments in metaheuristics; adaptation of discrete metaheuristics to continuous optimization; performance comparisons of metaheuristics; cooperative methods combining different approaches; parallel and distributed metaheuristics for multiobjective optimization; software implementations; and real-world applications.

This book is suitable for practitioners, researchers and graduate students in disciplines such as optimization, heuristics, operations research, and natural computing.

Evolution is Nature’s design process. The natural world is full of wonderful examples of its successes, from engineering design feats such as powered flight, to the design of complex optical systems such as the mammalian eye, to the merely stunningly beautiful designs of orchids or birds of paradise. With increasing computational power, we are now able to simulate this process with greater fidelity, combining complex simulations with high-performance evolutionary algorithms to tackle problems that used to be impractical.

This book showcases the state of the art in evolutionary algorithms for design. The chapters are organized by experts in the following fields: evolutionary design and "intelligent design" in biology, art, computational embryogeny, and engineering. The book will be of interest to researchers, practitioners and graduate students in natural computing, engineering design, biology and the creative arts.