Hands-On Neuroevolution with Python

Overview of the neuroevolution methods

In this chapter, we learned about the core concepts of genetic algorithms, such as genetic operators and genome encoding schemes.

We discussed two major genetic operators that allow us to maintain the evolutionary process:

• The mutation operator implements random mutations of the offspring, which introduces genetic diversity into the population.
• The crossover operator generates offspring by sampling genes from each parent.

After that, we continued with a discussion about the importance of choosing the right genome encoding schema. We considered two major encoding formats that exist: direct and indirect genome encoding. The former introduces a one-to-one relationship between the genome and the encoded ...