David B. Fogel

toward a new philosophy of machine intelligence

Evolutionary computation

Zbigniew Michalewicz

No pleasure lasts long unless there is variety in it. Publilius Syrus, Moral Sayings We've been very fortunate to receive fantastic feedback from our readers during the last four years, since the first edition of How to Solve It: Modern Heuristics was published in 1999. It's heartening to know that so many people appreciated the book and, even more importantly, were using the book to help them solve their problems. One professor, who published a review of the book, said that his students had given the best course reviews he'd seen in 15 years when using our text. There can be hardly any better praise, except to add that one of the book reviews published in a SIAM journal received the best review award as well. We greatly appreciate your kind words and personal comments that you sent, including the few cases where you found some typographical or other errors. Thank you all for this wonderful support.

How to Solve It: Modern Heuristics

Charles J. Robinson

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 Experts Speak

Computational Intelligence

James C. Bezdek

Bruno Bosacchi

28-29 July 1997, San Diego, California

Applications of Soft Computing

Evolutionary cmputation is one of the fastest growing areas of computer science, partly because of its broad applicability to engineering problems. The methods can be applied to problems as diverse as supply-chain optimization, routing and planning, task assignment, pharmaceutical design, interactive gaming, and many others within the signal processing domain.

Principles and Practice for Signal Processing

Evolutionary Computation

This book explains how a computer, by replicating the processes of Darwinian evolution, taught itself to play checkers far better than its creators could have programmed it to play. Fogel (editor, IEEE Transactions on Evolutionary Computation) considers the implications for evolutionary computations and artificial intelligence. Diagrams illustrate the evolutionary and computational processes at work, and the course of various games of checkers. Annotation copyrighted by Book News, Inc., Portland, OR.

Playing at the Edge of AI

Blondie24

This Third Edition provides the latest tools and techniques thatenable computers to learn The Third Edition of this internationally acclaimed publicationprovides the latest theory and techniques for using simulatedevolution to achieve machine intelligence. As a leading advocatefor evolutionary computation, the author has successfullychallenged the traditional notion of artificial intelligence, whichessentially programs human knowledge fact by fact, but does nothave the capacity to learn or adapt as evolutionary computationdoes. Readers gain an understanding of the history of evolutionarycomputation, which provides a foundation for the author's thoroughpresentation of the latest theories shaping current research.Balancing theory with practice, the author provides readers withthe skills they need to apply evolutionary algorithms that cansolve many of today's intransigent problems by adapting to newchallenges and learning from experience. Several examples areprovided that demonstrate how these evolutionary algorithms learnto solve problems. In particular, the author provides a detailedexample of how an algorithm is used to evolve strategies forplaying chess and checkers. As readers progress through the publication, they gain anincreasing appreciation and understanding of the relationshipbetween learning and intelligence. Readers familiar with theprevious editions will discover much new and revised material thatbrings the publication thoroughly up to date with the latestresearch, including the latest theories and empirical properties ofevolutionary computation. The Third Edition also features new knowledge-building aids.Readers will find a host of new and revised examples. New questionsat the end of each chapter enable readers to test their knowledge.Intriguing assignments that prepare readers to manage challenges inindustry and research have been added to the end of each chapter aswell. This is a must-have reference for professionals in computer andelectrical engineering; it provides them with the very latesttechniques and applications in machine intelligence. With itsquestion sets and assignments, the publication is also recommendedas a graduate-level textbook.

Toward a New Philosophy of Machine Intelligence

Although evolutionary computation has only been a popular topic for the last 20 years, it actually has antecedents back in the '50s. This is the first text to present the most significant and historic papers on evolutionary computation ranging from the '50s to the early '90s. Features a comprehensive bibliography of the available literature in the field.

David B. Fogel

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