Электронная книга: Dan Simon «Evolutionary Optimization Algorithms»
|
A clear and lucid bottom-up approach to the basic principles of evolutionary algorithms Evolutionary algorithms (EAs) are a type of artificial intelligence. EAs are motivated by optimization processes that we observe in nature, such as natural selection, species migration, bird swarms, human culture, and ant colonies. This book discusses the theory, history, mathematics, and programming of evolutionary optimization algorithms. Featured algorithms include genetic algorithms, genetic programming, ant colony optimization, particle swarm optimization, differential evolution, biogeography-based optimization, and many others. Evolutionary Optimization Algorithms: Provides a straightforward, bottom-up approach that assists the reader in obtaining a clear—but theoretically rigorous—understanding of evolutionary algorithms, with an emphasis on implementation Gives a careful treatment of recently developed EAs—including opposition-based learning, artificial fish swarms, bacterial foraging, and many others— and discusses their similarities anddifferences from more well-established EAs Includes chapter-end problems plus a solutions manual available online for instructors Offers simple examples that provide the reader with an intuitive understanding of the theory Features source code for the examples available on the author's website Provides advanced mathematical techniques for analyzing EAs, including Markov modeling and dynamic system modeling Evolutionary Optimization Algorithms: Biologically Inspired and Population-Based Approaches to Computer Intelligence is an ideal text for advanced undergraduate students, graduate students, and professionals involved in engineering and computer science. Издательство: "John Wiley&Sons Limited"
ISBN: 9781118659502 электронная книга Купить за 10269.66 руб и скачать на Litres |
Другие книги автора:
| Книга | Описание | Год | Цена | Тип книги |
|---|---|---|---|---|
| Evolutionary Computation with Biogeography-based Optimization | Evolutionary computation algorithms are employed to minimize functions with large number of variables. Biogeography-based optimization (BBO) is an optimization algorithm that is based on the science… — John Wiley&Sons Limited, электронная книга Подробнее... | электронная книга |
См. также в других словарях:
Category:Optimization algorithms — An optimization algorithm is an algorithm for finding a value x such that f(x) is as small (or as large) as possible, for a given function f, possibly with some constraints on x. Here, x can be a scalar or vector of continuous or discrete values … Wikipedia
Ant colony optimization algorithms — Ant behavior was the inspiration for the metaheuristic optimization technique. In computer science and operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems which can be… … Wikipedia
Evolutionary informatics — is a subfield of informatics addressing the practice of information processing in, and the engineering of information systems for, the study of biological evolution, as well as the study of information in evolutionary systems, natural and… … Wikipedia
Evolutionary algorithm — In artificial intelligence, an evolutionary algorithm (EA) is a subset of evolutionary computation, a generic population based metaheuristic optimization algorithm. An EA uses some mechanisms inspired by biological evolution: reproduction,… … Wikipedia
Evolutionary computation — For the journal, see Evolutionary Computation (journal). In computer science, evolutionary computation is a subfield of artificial intelligence (more particularly computational intelligence) that involves combinatorial optimization problems.… … Wikipedia
Meta-optimization — concept. In numerical optimization, meta optimization is the use of one optimization method to tune another optimization method. Meta optimization is reported to have been used as early as in the late 1970s by Mercer and Sampson [1] for finding… … Wikipedia
