This "Third Edition" provides the latest tools and techniques that enable computers to learn

The "Third Edition" of this internationally acclaimed publication provides the latest theory and techniques for using simulated evolution to achieve machine intelligence. As a leading advocate for evolutionary computation, the author has successfully challenged the traditional notion of artificial intelligence, which essentially programs human knowledge fact by fact, but does not have the capacity to learn or adapt as evolutionary computation does.

Readers gain an understanding of the history of evolutionary computation, which provides a foundation for the author's thorough presentation of the latest theories shaping current research. Balancing theory with practice, the author provides readers with the skills they need to apply evolutionary algorithms that can solve many of today's intransigent problems by adapting to new challenges and learning from experience. Several examples are provided that demonstrate how these evolutionary algorithms learn to solve problems. In particular, the author provides a detailed example of how an algorithm is used to evolve strategies for playing chess and checkers.

As readers progress through the publication, they gain an increasing appreciation and understanding of the relationship between learning and intelligence. Readers familiar with the previous editions will discover much new and revised material that brings the publication thoroughly up to date with the latest research, including the latest theories and empirical properties of evolutionary computation.

The "Third Edition" also features new knowledge-building aids. Readers will find a hostof new and revised examples. New questions at the end of each chapter enable readers to test their knowledge. Intriguing assignments that prepare readers to manage challenges in industry and research have been added to the end of each chapter as well.

This is a must-have reference for professionals in computer and electrical engineering; it provides them with the very latest techniques and applications in machine intelligence. With its question sets and assignments, the publication is also recommended as a graduate-level textbook.

The definitive survey of computational intelligence from luminaries in the field

Computational intelligence is a fast-moving, multidisciplinary field–the nexus of diverse technical interest areas that include neural networks, fuzzy logic, and evolutionary computation. Keeping up with computational intelligence means understanding how it relates to an ever-expanding range of applications. This is the book that ties it all together–and puts that understanding well within your reach.

In Computational Intelligence: The Experts Speak, editors David B. Fogel and Charles J. Robinson present an unmatched compilation of expanded papers from plenary and special lecturers attending the 2002 IEEE World Congress on Computational Intelligence. Collectively, these papers provide a compelling snapshot of the issues that define the industry, as observed by some of the top minds in the computational intelligence community. In a series of topical chapters, this comprehensive volume shows how current technology is shaping computational intelligence, and it delivers eye-opening insights into the field’s future challenges.

The research detailed here covers an array of leading-edge applications, from coevolutionary robotics to underwater sensors and cognitive science, in such areas as:

• Self-organizing systems
• Situation awareness
• Human-machine interaction
• Automatic control
• Data recognition

Computational Intelligence also includes introductions to each grouping of contributions that provide helpful tutorials and discuss important parallels between topics.

Whatever your role might be in this dynamic, influential field, this is the one reference that no practitioner of computational intelligence should be without.

The field of evolutionary computation is expanding dramatically, fueled by the vast investment that reflects the value of applying its techniques. Culling material from the Handbook of Evolutionary Computation, Evolutionary Computation 1: Basic Algorithms and Operators contains up-to-date information on algorithms and operators used in evolutionary computing. This volume discusses the basic ideas that underlie the main paradigms of evolutionary algorithms, evolution strategies, evolutionary programming, and genetic programming. It is intended to be used by individual researchers, teachers, and students working and studying in this expanding field.

The field of evolutionary computation is expanding dramatically, fueled by the vast investment that reflects the value of applying its techniques. Culling material from the Handbook of Evolutionary Computation, Evolutionary Computation 1: Basic Algorithms and Operators contains up-to-date information on algorithms and operators used in evolutionary computing. This volume discusses the basic ideas that underlie the main paradigms of evolutionary algorithms, evolution strategies, evolutionary programming, and genetic programming. It is intended to be used by individual researchers, teachers, and students working and studying in this expanding field.