Hands-On Genetic Algorithms with Python

Mutation operator

We will now reset our changes again, as we get ready to experiment with the mutation operator, which is responsible for introducing random modifications to offspring:

1. We will start by increasing the value of the P_MUTATION constant to 0.9. This results in the following plot:

Stats of the program solving the OneMax problem after increasing the mutation probability to 0.9

The results may seem surprising at first, as increasing the mutation rate typically causes the algorithm to behave erratically, while here the effect is seemingly unnoticeable. However, recall that there is another mutation-related parameter in our algorithm, ...