An Introduction to Genetic Algorithms.
An Introduction to Genetic Algorithms.
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DOI：
10.1162/artl.1997.3.1.63
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发表时间：
1997
期刊：
影响因子：
2.6
通讯作者：
D. Heiss-Czedik
中科院分区：
文献类型：
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作者：
D. Heiss-Czedik
《遗传算法导论》是少有的每一页都值得一读的书。作者梅勒妮·米切尔（Melanie Mitchell）设法深入描述了许多引人入胜的例子和重要的理论问题，但这本书简明扼要（200页），可读性强。尽管米切尔明确表示，她的目的不是全面调查，但遗传算法（GAs）的基本内容包括：理论和实践，问题解决和科学模型，“简史”和“未来方向”。她的书既是对GAs感兴趣的新手的介绍，也是最近研究的集合，包括共同进化（种间和种内），二倍体和显性，封装，分层调节，自适应编码，学习和进化的相互作用，自适应GAs等热门话题。然而，这本书更多地关注机器学习、人工生命和建模进化，而不是优化和工程。
An Introduction to Genetic Algorithms is one of the rare examples of a book in which every single page is worth reading. The author, Melanie Mitchell, manages to describe in depth many fascinating examples as well as important theoretical issues, yet the book is concise (200 pages) and readable. Although Mitchell explicitly states that her aim is not a complete survey, the essentials of genetic algorithms (GAs) are contained: theory and practice, problem solving and scientific models, a "Brief History" and "Future Directions." Her book is both an introduction for novices interested in GAs and a collection of recent research, including hot topics such as coevolution (interspecies and intraspecies), diploidy and dominance, encapsulation, hierarchical regulation, adaptive encoding, interactions of learning and evolution, self-adapting GAs, and more. Nevertheless, the book focused more on machine learning, artificial life, and modeling evolution than on optimization and engineering.