Genetic Algorithms

Practice Exercise from “evolving faces” example

Description

I based my exercise on this example from Nature of Code’s material by Daniel Shiffman. My original idea was to create two sets of parents where the user can adjust the characteristics of each one. Each one of these two sets of parents would have one child that together would create a third generation.

However, I accomplished only the creation of one set of parents where the user can modify the appearance and the fitness (probability of inheritance) and see how this influences their child. My goal was to understand the process and how the code works.

Link to Code

Process

I spent most of the time watching and reading the resources, trying to understand the concept of genetic algorithms. To be honest, I think I barely understood how it is applied. Most of the challenges that I experienced are that it is a concept based on multiple abstract processes.
To better understand, I kept my learning process close to the exercise.

Concept

I was watching a few simulation projects where the objective is to mimic natural movement or changes. This is basically a reaction of being critical of how robotic my animals looked in my last assignment. Interestingly, I was searching for stimulating evolving environments before this week. I found some YouTube videos from Primer like Your genes are selfish. But are you?
I was wondering, how would it be possible to create a simulation that evolves by itself? I haven't yet a clear idea of what this means in my own process, but it is something that I want to keep exploring.