Learning in Matrix Games can be Arbitrarily Complex

Gabriel P. Andrade, Rafael Frongillo, Georgios Piliouras

A growing number of machine learning architectures, such as Generative Adversarial Networks, rely on the design of games which implement a desired functionality via a Nash equilibr…