AI Researchers Produce New Kind of PC Game
Ken Stanley writes "In an unusual demonstration of video game innovation with limited
funding and resources, a mostly volunteer team of over 30 student
programmers, artists, and researchers at the University of Texas at
Austin has produced a new game genre in which the
player interacively trains robotic soldiers for combat. Unlike most games
today that use scripting for the AI, non-player-characters in NERO learn
new tactics in real-time using advanced machine learning techniques.
Perhaps projects such as this one will encourage the video game
industry to begin to seek alternatives to simple scripted AI."
Slashdotted before it even went live. Here is a working link. Downloads are currently at 511, I hope their counter has more than 9 bits...
This isn't entirely a new idea. CROBOTS, for example, put one in the position of designing AIs that control tanks and then pits them against one another in an arena.
It would be a lot easier to train a robot to train the other robots to fight (in the long run)...Wouldn't it?
It's been done before.
Apologies to the submitter!
Only for the purposes of helping distribution, and for a limited time, torrent available at nerogame.exe.torrent
Visit Lockjaw's Lair. He won't bite.
False.
FLOPs are not generally useful for things like scripted AI which are very branch heavy with a lot of indirection, and many possible branch targets and data requirements.
The techniques described in this game are highly mathematical in nature with a small memory foot-print, (adaptive neural networks and genetic programming via Kenneth Stanley's NEAT algorithm) and would benefit hugely from parallel vector proccessing.
Additionally, at the end of the day, the AI decision making is not nearly as expensive as the proximity-query and pathfinding routines that affect the decisions. These routines also benefit hugely from vector processors and high bus-bandwidth.
So fittingly, the AI will only suffer if the human intelligence can't adapt and make the fairly obvious decision to move toward more mathematical AI routines.
This will seem even more like a flame but I can't think how else to word it.
In Iraq, the uk lost more troops to US "friendly fire" than to the Iraqis.
Unfortunately I'm not taking the piss.
> Call me short sighted, but isn't it at least possible that training soldiers is different to training tic-tac-toe players?
Yes. Tic-tac-toe has a manageable decision tree, and all MENACE did was prune branches that led to losing. It still required many playings, because it always pruned at the last decision that led to the loss. (Thus it trimmed the decision tree from back to front.) It would be completely untractable for chess, let alone for continuous-state games or simulations.
Still, MENACE was a brilliant insight for the time. IIRC it was done way back in the 50's -- practically the beginning of time so far as computer science is concerned -- and brought to public attention when Martin Gardner covered it in his Scientific American column in the early 60's.
Sheesh, evil *and* a jerk. -- Jade
Will these things be marketable? "Ma, I'm not playing games, I'm training my robo-warrior!"