Deep reinforcement learning methods implemented in tensorflow2
python>=3.7, tensorflow>=2.1, ray>=1.0
Playing Atari with Deep Reinforcement Learning (2013)
Human-level control through deep reinforcement learning (2015)
Deep Reinforcement Learning with Double Q-learning
Dueling Network Architectures for Deep Reinforcement Learning
A Distributional Perspective on Reinforcement Learning
Rainbow: Combining Improvements in Deep Reinforcement Learning
Distributional Reinforcement Learning with Quantile Regression
Fully Parameterized Quantile Function for Distributional Reinforcement Learning
Distributed Prioritized Experience Replay
Recurrent Experience Replay in Distributed Reinforcement Learning
Asynchronous Methods for Deep Reinforcement Learning
Deterministic Policy Gradient Algorithms
Continuous control with deep reinforcement learning
Addressing Function Approximation Error in Actor-Critic Methods
Trust Region Policy Optimization
Proximal Policy Optimization Algorithms
Soft Actor-Critic Algorithms and Applications、Haarnoja et al、2018
A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play
Mastering the game of Go without human knowledge
Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model
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