Hierarchical Bayesian optimization algorithm toward a new generation of evolutionary algorithms /
"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 book focuses on two algorithms that replace traditional variation operators of evolutionary algorithms by lear...
| Main Author: | Pelikan, Martin. |
|---|---|
| Other Authors: | SpringerLink (Online service) |
| Format: | eBook |
| Language: | English |
| Published: |
Berlin ; New York :
Springer-Verlag,
2005.
Berlin ; New York : 2005. |
| Physical Description: |
1 online resource (xviii, 166 pages) : illustrations. |
| Edition: | 1st ed. |
| Series: |
Studies in fuzziness and soft computing ;
170. |
| Subjects: |
Table of Contents:
- From Genetic Variation to Probabilistic Modeling
- Probabilistic Model-Building Genetic Algorithms
- Bayesian Optimization Algorithm
- Scalability Analysis
- The Challenge of Hierarchical Difficulty
- Hierarchical Bayesian Optimization Algorithm
- Hierarchical BOA in the Real World.