Digital Trends:

“In [our new] work, we wanted to understand how AI agents could learn about a realistic environment by playing an interactive game within it,” Weihs said. “To answer this question, we trained two agents to play Cache, a variant of hide-and-seek, using adversarial reinforcement learning within the high-fidelity AI2-THOR environment. Through this gameplay, we found that our agents learned to represent individual images, approaching the performance of methods requiring millions of hand-labeled images — and even began to develop some cognitive primitives often studied by [developmental] psychologists.”
Why Scientists are Teaching Robots to Play Hide-and-Seek | Digital Trends
Artificial intelligence can do a lot of amazing things these days, but it’s still not smart enough to play a simple game of hide and seek. Not yet, that is