A team of scientists at Uber’s artificial intelligence lab just pulled off one of the major outstanding challenges in AI research — something so advanced and difficult that some wondered whether an AI system would ever figure it out.
This article was originally published on Futurism. This is just a theme demo site.
That’s right. The team, the MIT Technology Review reports, built an algorithm that’s really, really good at old-school video games “Pitfall!” and “Montezuma’s Revenge.”
And while it did take some help from humans, according to Uber’s blog post on the soon-to-be-published research, the algorithm learned to rack up scores no human player could ever reach.
Team work is important
When AI learns how to play and subsequently master a video game, it’s often by way of reinforcement learning, a type of algorithm that learns to seek out things that it has been programmed to treat as a reward. An ever-rising video game score makes for eager reinforcement learning-driven AI gamers, but games like “Pitfall!” and “Montezuma’s Revenge” don’t immediately (or often) increase the player’s score, MIT Tech Reviewmentions.