Hi Jin,
As for the LSTM input, it uses the activations (not parameters) from the previous network layer at the current time as its main input. It handles the "time series" aspect by combining this with its internal hidden state (its memory) from the previous time step.
Therefore, it processes observations one by one, not all at once. As for the RL agents that can use LSTMs, the main ones are DQN, PPO, A2C, DDPG, SAC, and TD3.
Some resources and examples that may be helpful
