Game theory as an engine for large-scale data analysis

Modern AI systems approach tasks like recognising objects in images and predicting the 3D structure of proteins as a diligent student would prepare for an exam. By training on many example problems, they minimise their mistakes over time until they achieve success. But this is a solitary endeavour and only one of the known forms of learning. Learning also takes place by interacting and playing with others. It’s rare that a single individual can solve extremely complex problems alone. By allowing problem solving to take on these game-like qualities, previous DeepMind efforts have trained AI agents to play Capture the Flag and achieve Grandmaster level at Starcraft. This made us wonder if such a perspective modeled on game theory could help solve other fundamental machine learning problems.