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README.md

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@@ -33,7 +33,7 @@ In these tutorials for reinforcement learning, it covers from the basic RL algor
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* [A3C](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/10_A3C)
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* [Dyna-Q](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/11_Dyna_Q)
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* [Proximal Policy Optimization (PPO)](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/12_Proximal_Policy_Optimization)
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* [Curiosity Model](/contents/Curiosity_Model)
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* [Curiosity Model](/contents/Curiosity_Model), [Random Network Distillation (RND)](/contents/Curiosity_Model/Random_Network_Distillation.py)
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* [Some of my experiments](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/experiments)
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* [2D Car](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/experiments/2D_car)
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* [Robot arm](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/experiments/Robot_arm)

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