Patent ID: 11868882
Assignee: DEEPMIND TECHNOLOGIES LIMITED
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 9:
10. The method of training a reinforcement learning system to select actions to be performed by an agent interacting with an environment to perform a task, the method comprising:
capturing training data from a demonstration of the task within the environment, the training data defining demonstration transition data for a series of demonstration transitions, each transition comprising state data characterizing a state of the environment, action data defining an action performed, reward data representing a reward from the action, and new state data representing a new state, wherein the action data defines one or more actions in a continuous action space, and wherein the environment transitions to the new state in response to the action;
storing the demonstration transition data in a replay buffer;
operating on the environment with an actor-critic system to generate operation transition data comprising operational examples of the state data, the action data, the reward data and the new state data;
storing the operation transition data in the replay buffer;
sampling a plurality of stored tuples from the replay buffer, the sampled tuples comprising tuples from both the operation transition data and the demonstration transition data; and
training the actor-critic system using the sampled tuples.