Evolution 2.0

Enter full screen for the  best experience. 

This simulation is based on a genetic algorithm wherein a population of creatures try to make their way to the target. Each creature has a set of genes that determine it's movement direction and size.

Each creature has a fitness score which is calculated based on the individuals proximity to the target at the end of each generation. Individuals with a higher score are more likely to be added to the breeding population to pass on their superior genes to the next generation.

This project showcases the utility of machine learning, more specifically  a genetic algorithm. This project was made in Unity using c#.