Introducing Evolutionary Systems
Evolutionary algorithms are a family of stochastic techniques for solving problems that are part of the broader category of natural metaphor models. They find their inspiration in biology and are based on the imitation of the mechanisms of so-called natural evolution. Over the last few years, these techniques have been applied to many problems of great practical importance.
In this chapter, we will learn the basic concepts of SC and how to implement genetic programming. We will also understand the genetic algorithm techniques, how to implement symbolic regression, and how to use the cellular automata (CA) model.
In this chapter, we’re going to cover the following main topics:
- Introducing SC
- Understanding genetic programming
- Applying a genetic algorithm for search and optimization
- Performing symbolic regression
- Exploring the CA model
