Portfolio Assignment 9

For our final project we took a closer look at the N.E.R.O. machine learning game. N.E.R.O. stands for Neuro-Evolving Robotic Operatives. The game allows the user to train a team of robots to perform simple tasks, like going around a wall.

When the training your robots for the first time, your troops just run around. This is because the troops have not been trained to do anything. The first step is to put a static enemy in and reward your troops for approaching the enemy and firing upon the enemy. Next the user can put a wall between the troops, so the robots cannot see the enemy. Depending on how your robots are rewarded, your troops should start to navigate around the wall and fire upon the enemy. After this task, you can start to train your troops to defeat a maze, a turret and even a group of moving enemies.

There were several setbacks while using N.E.R.O., such as N.E.R.O. crashing every twenty minutes of use. This was a major setback because time is needed when training your robots to do certain tasks. We wanted to be able to start the training and let the troops learn overnight and with the crashing of the program we couldn't do it. Another set back was the intensive calculations required on for the program to run, which made running N.E.R.O. hard to do on my laptop for more than a few minutes at a time without the laptop heat way up. 

I enjoyed using N.E.R.O. and I found it interesting to see the robots learning. After training for an hour I compared my troops to untrained troops and the difference was amazing. If we were able to allow the program to run for 24 hours with converging the brains of the fittest robot every five minutes we would see the extent of the training capabilities of N.E.R.O..