Uber’s AI plays text-based games like a human

Can AI learn to play text-based games like a human? That’s the question applied scientists at Uber’s AI research division set out to answer in a recent study. Their exploration and imitation-learning-based system — which builds upon an earlier framework called Go-Explore — taps policies to solve a game by following paths (or trajectories) with high rewards.

“Text-based computer games describe their world to the player through natural language and expect the player to interact with the game using text. These games are of interest as they can be seen as a testbed for language understanding, problem-solving, and language generation by artificial agents,” wrote the coauthors of a paper describing the work. “Moreover, they provide a learning environment in which these skills can be acquired through interactions with an environment rather than using fixed corpora … [That’s why] existing methods for solving text-based games are limited to games that are either very simple or have an action space restricted to a predetermined set of admissible actions.”