LSTM

Long Short-Term Memory — a recurrent neural network architecture with memory cells and gating mechanisms (input, forget, output gates) that can learn long-term temporal dependencies. LSTMs are used in robot policies that need to integrate information over time, such as tasks requiring memory of past observations or multi-step reasoning. They have been largely superseded by transformers for sequence modeling.