Short bio: Computer Scientist, FOSS supporter (read more)
Tux Machines (TM)-specific
If you've ever been frustrated with the artificial intelligence (AI) in video games, then you are a prime candidate for Neuro-Evolving Robotic Operatives (N.E.R.O.), a cross-platform combat game where the key to winning is training your own intelligent non-player characters. On the field of play, the only rule is "let the best AI win." I tested my skills with the Linux client, and found N.E.R.O. to be a very different sort of game.
N.E.R.O. was first developed in 2003 at the University of Texas at Austin (UT). At UT's 2003 GameDev conference, AI researcher Ken Stanley proposed a game based around the idea of training soldier robots in real time, then pitting them against each other. It grew into an ongoing research project that involves a number of UT faculty and students.
The game has two distinct modes. In training mode, you play in a virtual sandbox, setting up enemies and obstacles, then unleashing your robot teams on them. The robots use neural networks to respond to game events, so you teach them by issuing rewards or penalties for events such as hitting a target, avoiding getting hit themselves, and standing their ground.
When you think you have a decent team, you can save your work and enter battle mode.