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A unique, one-stop reference to the history, technology, and application of evolutionary programming Evolutionary programming has come a long way since Lawrence Fogel first proposed in 1961 that intelligence could be modeled on the natural process of evolution. Efforts to apply this innovative approach to artificial intelligence have also evolved over the years, and the advent of fast desktop computers capable of solving complex computational problems has spawned an explosion of interest in the field. Offering the unique perspective of one of the inventors of evolutionary programming, this remarkable work traces forty years of developments in the field. Dr. Fogel consolidates a wealth of inf...
February 29-March 3, 1996, San Diego, California Evolutionary programming, originally conceived by Lawrence J. Fogel in 1960, is a stochastic and optimization method similar to genetic algorithms, but instead emphasizes the behavioral linkage between parents and their offspring, rather than emulating specific genetic operators as observed in nature. Evolutionary Programming V will serve as a reference and forum for researchers investigating applications and theory of evolutionary programming and other related areas in evolutionary and natural computation. Chapters describe original, unpublished research in evolutionary programming, evolution strategies, genetic algorithms and genetic program...
The main topics covered at this conference include evolutionary programming, evolution strategies and genetic algorithms. Specific research articles investigate applications in control, image processing, neural networks, artificial life and theoretical properties of optimization algorithms based on inspirations from biology. This volume provides researchers and graduate students with an update of developments in the field.
The main topics covered at this conference include evolutionary programming, evolution strategies and genetic algorithms. Specific research articles investigate applications in control, image processing, neural networks, artificial life and theoretical properties of optimization algorithms based on inspirations from biology. This volume provides researchers and graduate students with an update of developments in the field.
One of the most profound insights of the dynamic systems perspective is that new structures resulting from the developmental process do not need to be planned in advance, nor is it necessary to have these structures represented in genetic or neurological templates prior to their emergence. Rather, new structures can emerge as components of the individual and the environment self-organize; that is, as they mutually constrain each other's actions, new patterns and structures may arise. This theoretical possibility brings into developmental theory the important concept of indeterminism--the possibility that developmental outcomes may not be predictable in any simple linear causal way from their...
"Evolutionary Design By Computers offers an enticing preview of the future of computer-aided design: Design by Darwin." Lawrence J. Fogel, President, Natural Selection, Inc. "Evolutionary design by computers is the major revolution in design thinking of the 20th century and this book is the best introduction available." Professor John Frazer, Swire Chair and Head of School of Design, the Hong Kong Polytechnic University, Author of "An Evolutionary Architecture" "Peter Bentley has assembled and edited an important collection of papers that demonstrate, convincingly, the utility of evolutionary computation for engineering solutions to complex problems in design." David B. Fogel, Editor-in-Chie...
Joshua Fogel offers an incisive historical look at Sino-Japanese relations from three different perspectives. Introducing the concept of "Sinosphere" to capture the nature of Sino-foreign relations both spatially and temporally, Fogel presents an original and thought-provoking study on the long, complex relationship between China and Japan.
The first complete overview of evolutionary computing, the collective name for a range of problem-solving techniques based on principles of biological evolution, such as natural selection and genetic inheritance. The text is aimed directly at lecturers and graduate and undergraduate students. It is also meant for those who wish to apply evolutionary computing to a particular problem or within a given application area. The book contains quick-reference information on the current state-of-the-art in a wide range of related topics, so it is of interest not just to evolutionary computing specialists but to researchers working in other fields.