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Other titles in the Genetic Algorithms and Evolutionary Computation series:
Genetic Algorithms and Evolutionary Computation #7: The Design of Innovation: Lessons from and for Competent Genetic Algorithmsby David E. Goldberg
Synopses & Reviews
The Design of Innovation illustrates how to design and implement competent genetic algorithms-genetic algorithms that solve hard problems quickly, reliably, and accurately-and how the invention of competent genetic algorithms amounts to the creation of an effective computational theory of human innovation. For the specialist in genetic algorithms and evolutionary computation, this book combines over two decades of hard-won research results in a single volume to provide a comprehensive step-by-step guide to designing genetic algorithms that scale well with problem size and difficulty. For the innovation researcher - whether from the social and behavioral sciences, the natural sciences, the humanities, or the arts - this unique book gives a consistent and valuable mathematical and computational viewpoint for understanding certain aspects of human innovation. For all readers, The Design of Innovation provides an entrA(c)e into the world of competent genetic algorithms and innovation through a methodology of invention borrowed from the Wright brothers. Combining careful decomposition, cost-effective, little analytical models, and careful design, the road to competence is paved with easily understood examples, simulations, and results from the literature.
Book News Annotation:
Goldberg (U. of Illinois at Urbana-Champaign) brings together a genetic algorithms design methodology, applicable pieces of design theory, and genetic algorithms designs. He develops models that give explicit guidance on how to design genetic algorithms that work, what he calls "competent GAs." A basic understanding of calculus, probability, and statistics is suggested.
Annotation c. Book News, Inc., Portland, OR (booknews.com)
This volume shows readers how to design and implement genetic algorithms thatsolve hard problems quickly, reliably, and accurately.
This work illustrates how to design and implement competent genetic algorithms-genetic algorithms to solve hard problems quickly and reliably, and how the invention of competent genetic algorithms amounts to the creation of an effective computational theory of human innovation.
Includes bibliographical references (p. -240) and index.
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