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Genetic Algorithms in Search, Optimization, and Machine Learning
David Goldberg's Genetic Algorithms in Search, Optimization and Machine Learning is by far the bestselling introduction to genetic algorithms. Goldberg is one of the preeminent researchers in the field--he has published over 100 research articles o... |
Foundations of Genetic Programming
Genetic programming (GP), one of the most advanced forms of evolutionary computation, has been highly successful as a technique for getting computers to automatically solve problems without having to tell them explicitly how. Since its inceptions more tha... |
Introduction to Evolutionary Computing (Natural Computing Series)
Evolutionary Computing is the collective name for a range of problem-solving techniques based on principles of biological evolution, such as natural selection and genetic inheritance. These techniques are being increasingly widely applied to a variety of ... |
Genetic Programming : An Introduction : On the Automatic Evolution of Computer Programs and Its Applications (The Morgan Kaufmann Series in Artificial Intelligence)
Imagine a world in which computers program other computers based on strategies borrowed from biology and natural selection. Genetic Programming: An Introduction explores fascinating possibilities like these in a thriving area of computer-science re... |
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Intelligent Optimisation Techniques
This book covers four optimisation techniques loosely classified as intelligent: genetic algorithms, tabu search, simulated annealing and neural networks. Genetic algorithms locate optima using processes similar to those in natural selection and genetics.... |
Genetic and Evolutionary Computation - GECCO 2003 : Genetic and Evolutionary Computation Conference, Chicago, IL, USA, July 12-16, 2003, Proceedings, Part I (Lecture Notes in Computer Science)
The set LNCS 2723 and LNCS 2724 constitutes the refereed proceedings of the Genetic and Evolutionaty Computation Conference, GECCO 2003, held in Chicago, IL, USA in July 2003. The 193 revised full papers and 93 poster papers presented were carefully revie... |
The Design of Innovation (Genetic Algorithms and Evolutionary Computation)
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 t... |
Evolutionary Computation 1: Basic Algorithms and Operators (Evolutionary Computation)
The field of evolutionary computation is expanding dramatically, fueled by vast investment reflecting the value of applications of its techniques. The number of courses offered in evolutionary computing is growing rapidly: reflecting demand <... |
Spatial Evolutionary Modeling (Spatial Information Series)
Evolutionary models (e.g., genetic algorithms, artificial life), explored in other fields for the past two decades, are now emerging as an important new tool in GIS for a number of reasons. First, they are highly appropriate for modeling geographic pheno... |
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Multiobjective Scheduling by Genetic Algorithms
Multiobjective Scheduling by Genetic Algorithms describes methods for developing multiobjective solutions to common production scheduling equations modeling in the literature as flowshops, job shops and open shops. The methodology is metaheuri... |
Advances in Genetic Programming, Vol. 2 (Complex Adaptive Systems)
Genetic programming, a form of genetic algorithm that evolves programs and program-like executable structures, is a new paradigm for developing reliable, time- and cost-effective applications. The second volume of Advances in Genetic Programming hi... |
Hierarchical Bayesian Optimization Algorithm : Toward a New Generation of Evolutionary Algorithms (Studies in Fuzziness and Soft Computing)
This book provides a framework for the design of competent optimization techniques by combining advanced evolutionary algorithms with state-of-the-art machine learning techniques. The primary focus of the book is on two algorithms that replace traditional... |
Genetic Programming III: Darwinian Invention and Problem Solving
Genetic programming is a method for getting a computer to solve a problem by telling it what needs to be done instead of how to do it. Koza, Bennett, Andre, and Keane present genetically evolved solutions to dozens of problems of design, optimal contro... |
Evolutionary Algorithms in Theory and Practice: Evolution Strategies, Evolutionary Programming, Genetic Algorithms
This book presents a unified view of evolutionary algorithms: the exciting new probabilistic search tools inspired by biological models that have immense potential as practical problem-solvers in a wide variety of settings, academic, commercial, and indus... |
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Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic Algorithms and Evolutionary Computation)
The solving of multi-objective problems (MOPs) has been a continuing effort by humans in many diverse areas, including computer science, engineering, economics, finance, industry, physics, chemistry, and ecology, among others. Many powerful and determi... |
The Simple Genetic Algorithm: Foundations and Theory (Complex Adaptive Systems)
It might be simple, but it's not easy. Computer scientist Michael D. Vose takes a rigorous look at The Simple Genetic Algorithm and shows the state of our knowledge in a book appropriate for advanced undergraduates, graduate students, and professio... |
