GRU

Gated Recurrent Unit — a recurrent neural network architecture that uses gating mechanisms (reset and update gates) to selectively remember or forget information over time. GRUs are simpler than LSTMs with comparable performance. In robotics, GRUs are used in policies that require memory of past observations, such as POMDP settings where the full state is not observable.