To provide a reinforcement learning.SOLUTION: A method includes the steps of: maintaining respective episodic memory data for each of a plurality of actions; receiving current observation characterizing a current state of environment being interacted by an agent; processing the current observation by using an embedding neural network in accordance with current values of parameters of the embedding neural network to generate a current key embedding for the current observation; for each action of the plurality of actions, determining the p nearest key embeddings in the episodic memory data for the action to the current key embedding according to distance measurement; determining a Q value for the action from return estimates mapped to by the p nearest key embeddings in the episodic memory data for the action; and selecting, by using the Q values for the actions, an action from the plurality of actions as the action to be performed by the agent.SELECTED DRAWING: Figure 1
NEURAL EPISODIC CONTROL