A team of researchers at Uber AI Labs in San Francisco has developed a set of learning algorithms that proved to be better at playing Classic Video Game than human players or other AI systems. In their paper published in the journal Nature, the researchers explain how their algorithms differ from others and why they believe they have applications in robotics, language processing and even designing new drugs.
The researchers tested their new approach by adding game rules and a goal—score the most points possible and try to achieve a higher score every time. They then used their system to play 55 Atari games that, over time, have become benchmarks for testing AI systems. The new system beat other AI systems 85.5 percent of the time. It did particularly well at Montezuma’s Revenge, scoring higher than any other AI system and beating the record for a human. The researchers believe their algorithm could be ported to other applications such as image or language processing by robots.
