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tutorial-contents/405_DQN_Reinforcement_learning.py
@@ -74,6 +74,7 @@ def learn(self):
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# target parameter update
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if self.learn_step_counter % TARGET_REPLACE_ITER == 0:
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self.target_net.load_state_dict(self.eval_net.state_dict())
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+ self.learn_step_counter += 1
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# sample batch transitions
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sample_index = np.random.choice(MEMORY_CAPACITY, BATCH_SIZE)
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