Handbook of Evolutionary Machine Learning 9789819938148, 9789819938131
This book, written by leading international researchers of evolutionary approaches to machine learning, explores various
151 19 64MB
English Pages 784 Year 2023
- Author / Uploaded
- Wolfgang Banzhaf
- Penousal Machado
- Mengjie Zhang
- Categories
- Computers
- Cybernetics: Artificial Intelligence
Table of contents :
Cover
Front Matter
Part I. Evolutionary Machine Learning Basics
1. Fundamentals of Evolutionary Machine Learning
2. Evolutionary Supervised Machine Learning
3. EML for Unsupervised Learning
4. Evolutionary Computation and the Reinforcement Learning Problem
Part II. Evolutionary Computation as Machine Learning
5. Evolutionary Regression and Modelling
6. Evolutionary Clustering and Community Detection
7. Evolutionary Classification
8. Evolutionary Ensemble Learning
Part III. Evolution and Neural Networks
9. Evolutionary Neural Network Architecture Search
10. Evolutionary Generative Models
11. Evolution Through Large Models
12. Hardware-Aware Evolutionary Approaches to Deep Neural Networks
13. Adversarial Evolutionary Learning with Distributed Spatial Coevolution
Part IV. Evolutionary Computation for Machine Learning
14. Genetic Programming as an Innovation Engine for Automated Machine Learning: The Tree-Based Pipeline Optimization Tool (TPOT)
15. Evolutionary Model Validation—An Adversarial Robustness Perspective
16. Evolutionary Approaches to Explainable Machine Learning
17. Evolutionary Algorithms for Fair Machine Learning
Part V. Applications of Evolutionary Machine Learning
18. Evolutionary Machine Learning in Science and Engineering
19. Evolutionary Machine Learning in Environmental Science
20. Evolutionary Machine Learning in Medicine
21. Evolutionary Machine Learning for Space
22. Evolutionary Machine Learning in Control
23. Evolutionary Machine Learning in Robotics
24. Evolutionary Machine Learning in Finance
25. Evolutionary Machine Learning and Games
26. Evolutionary Machine Learning in the Arts
Back Matter
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