“AlphaStar is the first agent to achieve Grandmaster level in StarCraft II, and the first to reach the highest league of human players in a widespread professional esport without simplification of the game. Like StarCraft, real-world domains such as personal assistants, self-driving cars, or robotics require real-time decisions, over combinatorial or structured action spaces, given imperfectly observed information. Furthermore, similar to StarCraft, many applications have complex strategy spaces that contain cycles or hard exploration landscapes, and agents may encounter unexpected strategies or complex edge cases when deployed in the real world. The success of AlphaStar in StarCraft II suggests that general-purpose machine learning algorithms may have a substantial effect on complex real-world problems.”

Source : Grandmaster level in StarCraft II using multi-agent reinforcement learning | Nature