howitworks.txt

Neural Evolution is the result of several research about artificial intelligence.
The world that I created, using Processing, is composed by two elements: the Bloop and Food.
The Bloop (the white balls) walk and eat the food (red dots).

The Bloop have an initial health of 1000 points. Every time they eat, the health is increased by 100. If it goes to zero Bloop dies.

The Bloop are moved by a neural network shown in the image "brain.png". The inputs of the neural network are the distance along the X axis and the distance on the Y axis from the nearest food. While the outputs are the movement commands up, down, right, left.

All the weights of the network form the DNA of the individual Bloop, which is his way of interacting with the world.
Also in the DNA it is a further variable that indicates the magnitude of the Bloop and therefore its speed of movement.

At first all Bloop they are instantiated at random and as you can see in the video many do not know how to move or do incorrectly.

REPRODUCTION
Reproduction is asexual in every moment every Bloop has a small chance to reproduce, however, whether the Bloop is not healthy enough you can not play. Those who can breed have a green outline.
Therefore more a Bloop eats and survives more likely has to reproduce.
Reproducing create a Bloop with the same DNA but with some mutation of any gene or weight of the neural network.
What happens is that after several generations in the world there are only Bloop able to eat, and they are increasingly good at it.
The video shows only a few minutes of evolution, but if sent on for a long time improves.

At some point, however, they do not improve more because the world is very limited and there is nothing to learn.

[This is] therefore an example of a Neural Network trained through natural selection (genetic algorithm).