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- # Get Q values for next_state
- Qs_next_state = sess.run(TargetNetwork.output, feed_dict = {TargetNetwork.inputs_: next_states_mb})
- ...
- if tau > max_tau:
- # Update the parameters of our TargetNetwork with DQN_weights
- update_target = update_target_graph()
- sess.run(update_target)
- tau = 0
- print("Model updated")
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