Agents is a library for reinforcement learning in TensorFlow. 

importtensorflowastf
fromtf_agents.networksimport q_network
fromtf_agents.agents.dqnimport dqn_agent
q_net = q_network.QNetwork(
 train_env.observation_spec(),
 train_env.action_spec(),
 fc_layer_params=(100,))
agent = dqn_agent.DqnAgent(
 train_env.time_step_spec(),
 train_env.action_spec(),
 q_network=q_net,
 optimizer=optimizer,
 td_errors_loss_fn=common.element_wise_squared_loss,
 train_step_counter=tf.Variable(0))
agent.initialize()
 Run in a Notebook
TF-Agents makes designing, implementing and testing new RL algorithms easier, by providing well tested modular components that can be modified and extended. It enables fast code iteration, with good test integration and benchmarking.