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Lectures on Intelligent Systems / by Leonardo Vanneschi, Sara Silva
(Natural Computing Series. ISSN:26276461)
| データ種別 | 電子ブック |
|---|---|
| 版 | 1st ed. 2023. |
| 出版者 | (Cham : Springer International Publishing : Imprint: Springer) |
| 出版年 | 2023 |
| 大きさ | XIV, 349 p. 89 illus., 36 illus. in color : online resource |
| 著者標目 | *Vanneschi, Leonardo author Silva, Sara author SpringerLink (Online service) |
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| 一般注記 | Chapter 1: Introduction -- Chapter 2: Optimization Problems and Local Search -- Chapter 3: Genetic Algorithms -- Chapter 4: Particle Swarm Optimization -- Chapter 5: Introduction to Machine Learning -- Chapter 6: Decision Tree Learning -- Chapter 7: Artificial Neural Networks -- Chapter 8: Genetic Programming -- Bayesian Learning -- Chapter 10: Support Vector Machines -- Chapter 11: Ensemble Methods -- Chapter 12: Unsupervised Learning This textbook provides the reader with an essential understanding of computational methods for intelligent systems. These are defined as systems that can solve problems autonomously, in particular problems where algorithmic solutions are inconceivable for humans or not practically executable by computers. Despite the rapidly growing applications in this field, the book avoids application details, instead focusing on computational methods that equip the reader with the methodological tools and competencies necessary to tackle current and future complex applications. The book consists of two parts: computational intelligence methods for optimization, and machine learning. Part I begins with the concept of optimization, and introduces local search algorithms, genetic algorithms, and particle swarm optimization. Part II begins with an introduction to machine learning and covers several methods, many of which can be used as supervised learning algorithms, such as decision tree learning, artificial neural networks, genetic programming, Bayesian learning, support vector machines, and ensemble methods, plus a discussion of unsupervised learning. This textbook is written in a self-contained style, suitable for undergraduate or graduate students in computer science and engineering, and for self-study by researchers and practitioners HTTP:URL=https://doi.org/10.1007/978-3-031-17922-8 |
|---|---|
| 件 名 | LCSH:Artificial intelligence FREE:Artificial Intelligence |
| 分 類 | LCC:Q334-342 LCC:TA347.A78 DC23:006.3 |
| 書誌ID | EB00001305 |
| ISBN | 9783031179228 |
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※2019年3月27日以降