├── 2019_10_10_Asynchronous_Methods_for_Deep_Reinforcement_Learning.pdf ├── 2019_11_22_Stein_Variational_Gradient_Descent__A_General_Purpose_Bayesian_Inference_Algorithm.pdf ├── 2019_12_16_Learning_Representation_in_Reinforcement_Learning__An_Information_Bottleneck_Approach.pdf ├── 2020_02_07_AlphaGo_Zero.pdf ├── 2020_10_19_AlgaeDICE__Policy_Gradient_from_Arbitrary_Experience.pdf ├── 2020_10_21_Distributional_Reinforcement_Learning_with_Quantile_Regression.pdf ├── 2020_11_26_What_Matters_On_Policy_Deep_Actor_Critic_Method_A_Large_Scale_Study.pdf ├── 2021_01_22_Offline_Reinforcement_Learning_Review.pdf ├── 2021_03_09_DualDice__Behavior_Agnostic_Estimation_of_Discounted_Stationary_Distribution_Corrections (1).pdf ├── 2021_05_20_Reinforcement_Learning_via_Fenchel_Rockafellar_Duality.pdf ├── 2021_05_21_Adversarial_Policy_Training_against_Deep_Reinforcement_Learning.pdf ├── 2021_06_02_Machine_Learning_Testing__Survey_Landscapes_and_Horizon.pdf ├── 2021_06_02_Off_Policy_Evaluation_via_the_Regularized_Lagrangian.pdf ├── 2021_06_28_Does_Neuron_Coverage_Matter_for_Deep_Reinforcement_Learning__A_Preliminary_Study.pdf ├── 2021_09_23_Probability_Functional_Descent__A_Unifying_Perspective_on_GANs__Variational_Inference__and_Reinforcement_Learning.pdf ├── 2021_10_04_OptiDICE__Offline_Policy_Optimization_via_Stationary_Distribution_Correction_Estimation.pdf ├── 2022_01_18_EDGE__Explaining_Deep_Reinforcement_Learning_Policies.pdf ├── 2022_08_16_Overview_of_Model_Based_Reinforcement_Learning.pdf ├── Knowledge_2021_05_21_GAN_summary.pdf └── README.md /2019_10_10_Asynchronous_Methods_for_Deep_Reinforcement_Learning.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/2019ChenGong/RL-Paper-notes/HEAD/2019_10_10_Asynchronous_Methods_for_Deep_Reinforcement_Learning.pdf -------------------------------------------------------------------------------- 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/Knowledge_2021_05_21_GAN_summary.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/2019ChenGong/RL-Paper-notes/HEAD/Knowledge_2021_05_21_GAN_summary.pdf -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # RL-Paper-notes 2 | paper大家都可以在arxiv上找到。麻烦大家记得Star！ 3 | --------------------------------------------------------------------------------