This book describes the theory, operation, and application of genetic algorithms-search algorithms based on the mechanics of natural selection and genetics.
Genetic Algorithms in Search, Optimization, and Machine Learning
โ Scribed by David E. Goldberg
- Publisher
- Addison-Wesley Professional
- Year
- 1989
- Tongue
- English
- Leaves
- 432
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
This book brings together - in an informal and tutorial fashion - the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields. Major concepts are illustrated with running examples, and major algorithms are illustrated by Pascal computer programs. No prior knowledge of GAs or genetics is assumed, and only a minimum of computer programming and mathematics background is required. 0201157675B07092001
๐ SIMILAR VOLUMES
This book introduces the fundamental concepts of genetic algorithms in theory followed by a walk-through on the design and implementation of a genetic algorithms project.
<span>This book discusses state-of-the-art stochastic optimization algorithms for distributed machine learning and analyzes their convergence speed. The book first introduces stochastic gradient descent (SGD) and its distributed version, synchronous SGD, where the task of computing gradients is divi