This project is about simulating natural selection
to run the code, load the code in a same directory and run the main html file to modify the parameter, change the variables at beginning of the FinGeneAlgo.js file
All the processes have been outlined in the documentation genes = Their 2D vectors individuals = balls
Overview: We judge the capability of a species by their ability to reach a target. Generation 0 is spawned with random genes. Then, they are judged by theiir ability to get closer to the target higher fitness = closer to the target. individuals with high fitness are more likely to be chosen for mating. after generation 0 exhausts their genes, we mate them and spawn a new generation.
In theory, this should increase each generation's ability to reach their target. with each generation, the fitness score increses, thereby confirming darwin's theory of survival of the fittest
Here is a representation of how the simulation works:
As we can see that with each generation, we increase out total generation fitness and we get to the target. Hence, even though the mutations are random, we get stronger offsprings based on the principle of natural selection.