Artificial intelligence is getting smarter. In March, an A.I. platform named AlphaGo beat a human champion in the game of Go. Now the machines are prepping for their next big challenge: first-person shooter video games.
Later this year, the 2016 Computational Intelligence and Games (CIG) Conference will host an event in which bots will pummel each other in classic “Doom,” the 1993 blockbuster that established the template for a generation of action games.
The CIG event will feature two “tracks”: a limited match on a map known to the participants beforehand, in which bots can arm themselves with rocket launchers, and a full match on an unknown map, with every game weapon and item available.
“Although the participants are allowed to use any technique to develop a controller,” reads the competition’s rules, “the design and efficiency of the Visual Doom AI environment allows and encourages participants to use machine learning methods such as reinforcement deep learning.” (Those interested in participating can start by downloading the ViZDoom Environment from GitHub.)
Researchers aren’t just doing this for the thrill of watching a couple of bots blasting each other apart in a twenty-year-old video game. They want to see if bots can leverage tons of data—including gameplay patterns—to quickly become smarter and more effective at winning. It’s the same underlying principle employed by Google subsidiary DeepMind to build its Go-playing A.I. platform, only the medium in this case is rocket launchers and shotguns instead of black and white chips on a board.
And just think how invaluable all that first-person shooter knowledge will prove when the machines finally rise up against humanity.