AI learned to use tools after nearly 500 million games of hide and seek

To create the game, the researchers designed a virtual environment that consisted of an enclosed space with various objects like blocks, ramps, and mobile and immobile barricades. The agents themselves were controlled by reinforcement-learning algorithms. For each game, the agents were split into two teams: hiders were rewarded or penalized for avoiding or failing to avoid the seekers, respectively; seekers were also rewarded or penalized for finding or failing to find the hiders. As in a classic game of hide and seek, hiders were also given a few seconds' head start. The researchers gave the agents no other instructions.