NERO (which stands for Neuro-Evolving Robotic Operatives) is a new kind of machine learning game being developed at the Neural Networks Research Group, Department of Computer Sciences, University of Texas at Austin. The goals of the project are (1) to demonstrate the power of state-of-the-art machine learning technology, (2) to create an engaging game based on it, and (3) to provide a robust and challenging development and benchmarking domain for AI researchers.

NERO is an example of a new genre of games, called Machine Learning Games. Although it resembles some RTS games, there are three important differences: (1) in NERO the agents are embedded in a 3D physics simulation, (2) the agents are trainable, and (3) the game consists of two distinct phases of play. In the first phase individual players deploy agents, i.e. simulated robots, in a “sandbox” and train them to the desired tactical doctrine. Once a collection of robots has been trained, a second phase of play (either battle or territory mode) allows players to pit their robots in a battle against robots trained by some other player, to see how effective their training was. The training phase is the most innovative aspect of game play in NERO, and is also the most interesting from the perspective of AI research.

Make sure that the driver to your 3D graphic card is proper installed and working.

Download N.E.R.O. to your Desktop.

Download

Open up the terminal and type;

Code:

mkdir -p ~/.Games/nero
cd ~/Desktop
tar zxfv nero2_linux_i386.tar.gz
cd nero2_linux_i386
mv * ~/.Games/nero

Done.

Download nero.png to your Desktop;

Once more to the terminal;

Code:

nano ~/.Games/nero/NeroLaunch.sh

add the following

Save (ctrl)+(o) and exit (ctrl)+(x).

Code:

chmod +x ~/.Games/nero/NeroLaunch.sh
cd ~/Desktop
mv nero.png ~/.Games/nero
alacarte

Go to Games and make a new entry;

Enjoy!