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papers/readme.md

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 |                 | Continuous Control With Deep Reinforcement Learning (**DDPG**) | https://arxiv.org/abs/1509.02971              |          |
 |                 | Addressing Function Approximation Error in Actor-Critic Methods (**TD3**) [[Markdown]](https://github.com/datawhalechina/easy-rl/blob/master/papers/Policy_gradient/Addressing%20Function%20Approximation%20Error%20in%20Actor-Critic%20Methods.md) [[PDF]](https://github.com/datawhalechina/easy-rl/blob/master/papers/Policy_gradient/PDF/Addressing%20Function%20Approximation%20Error%20in%20Actor-Critic%20Methods.pdf) | https://arxiv.org/abs/1802.09477              |          |
 |                 | A Distributional Perspective on Reinforcement Learning (**C51**) [[Markdown]](https://github.com/datawhalechina/easy-rl/blob/master/papers/Policy_gradient/A%20Distributional%20Perspective%20on%20Reinforcement%20Learning.md) [[PDF]](https://github.com/datawhalechina/easy-rl/blob/master/papers/Policy_gradient/PDF/A%20Distributional%20Perspective%20on%20Reinforcement%20Learning.pdf) | https://arxiv.org/abs/1707.06887              |          |
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+|                 | Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic (**Q-Prop**) | https://arxiv.org/abs/1611.02247              |          |
+|                 | Action-depedent Control Variates for Policy Optimization via Stein’s Identity (**Stein Control Variates**) | https://arxiv.org/abs/1710.11198              |          |
+|                 | The Mirage of Action-Dependent Baselines in Reinforcement Learning | https://arxiv.org/abs/1802.10031              |          |
+|                 | Bridging the Gap Between Value and Policy Based Reinforcement Learning (**PCL**) | https://arxiv.org/abs/1702.08892              |          |
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