Computational Intelligence: An Introduction
This book was written by Andries Engelbrecht and published in 2007.
Computational Intelligence: An Introduction
This book provides an excellent overview of the field of nature-inspired optimization algorithms, also referred to as computational intelligence. This includes fields such as evolutionary computation and swarm intelligence.
This book is far less mathematical than the previous textbooks and is more focused on the metaphor of the inspired system and how to configure and use the specific algorithms with lots of pseudocode explanations.
While the material is introductory in nature, it does not shy away from details, and does present the mathematical foundations to the interested reader. The intention of the book is not to provide thorough attention to all computational intelligence paradigms and algorithms, but to give an overview of the most popular and frequently used models.
— Page xxix, Computational Intelligence: An Introduction, 2007.
Algorithms like genetic algorithms, genetic programming, evolutionary strategies, differential evolution, and particle swarm optimization are useful to know for machine learning model hyperparameter tuning and perhaps even model selection. They also form the core of many modern AutoML systems.
The complete table of contents for the book is listed below.
- Part I Introduction
- Chapter 01: Introduction to Computational Intelligence
- Part II Artificial Neural Networks
- Chapter 02: The Artificial Neuron
- Chapter 03: Supervised Learning Neural Networks
- Chapter 04: Unsupervised Learning Neural Networks
- Chapter 05: Radial Basis Function Networks
- Chapter 06: Reinforcement Learning
- Chapter 07: Performance Issues (Supervised Learning)
- Part III Evolutionary Computation
- Chapter 08: Introduction to Evolutionary Computation
- Chapter 09: Genetic Algorithms
- Chapter 10: Genetic Programming
- Chapter 11: Evolutionary Programming
- Chapter 12: Evolution Strategies
- Chapter 13: Differential Evolution
- Chapter 14: Cultural Algorithms
- Chapter 15: Coevolution
- Part IV Computational Swarm Intelligence
- Chapter 16: Particle Swarm Optimization
- Chapter 17: Ant Algorithms
- Part V Artificial Immune Systems
- Chapter 18: Natural Immune System
- Chapter 19: Artificial Immune Models
- Part VI Fuzzy Systems
- Chapter 20: Fuzzy Sets
- Chapter 21: Fuzzy Logic and Reasoning