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Title: GitHub - binaryknight/DeepRL: Modularized Implementation of Deep RL Algorithms in PyTorch · GitHub

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X Title: GitHub - binaryknight/DeepRL: Modularized Implementation of Deep RL Algorithms in PyTorch

Description: Modularized Implementation of Deep RL Algorithms in PyTorch - binaryknight/DeepRL

Open Graph Description: Modularized Implementation of Deep RL Algorithms in PyTorch - binaryknight/DeepRL

X Description: Modularized Implementation of Deep RL Algorithms in PyTorch - binaryknight/DeepRL

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README	https://github.com/binaryknight/DeepRL
MIT license	https://github.com/binaryknight/DeepRL
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DAC/Geoff-PAC/QUOTA/ACE	https://github.com/binaryknight/DeepRL#code-of-my-papers
v0.1	https://github.com/ShangtongZhang/DeepRL/releases/tag/v0.1
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	https://github.com/binaryknight/DeepRL#references
Human Level Control through Deep Reinforcement Learning	https://www.nature.com/nature/journal/v518/n7540/full/nature14236.html
Asynchronous Methods for Deep Reinforcement Learning	https://arxiv.org/abs/1602.01783
Deep Reinforcement Learning with Double Q-learning	https://arxiv.org/abs/1509.06461
Dueling Network Architectures for Deep Reinforcement Learning	https://arxiv.org/abs/1511.06581
Playing Atari with Deep Reinforcement Learning	https://arxiv.org/abs/1312.5602
HOGWILD!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent	https://arxiv.org/abs/1106.5730
Deterministic Policy Gradient Algorithms	http://proceedings.mlr.press/v32/silver14.pdf
Continuous control with deep reinforcement learning	https://arxiv.org/abs/1509.02971
High-Dimensional Continuous Control Using Generalized Advantage Estimation	https://arxiv.org/abs/1506.02438
Hybrid Reward Architecture for Reinforcement Learning	https://arxiv.org/abs/1706.04208
Trust Region Policy Optimization	https://arxiv.org/abs/1502.05477
Proximal Policy Optimization Algorithms	https://arxiv.org/abs/1707.06347
Emergence of Locomotion Behaviours in Rich Environments	https://arxiv.org/abs/1707.02286
Action-Conditional Video Prediction using Deep Networks in Atari Games	https://arxiv.org/abs/1507.08750
A Distributional Perspective on Reinforcement Learning	https://arxiv.org/abs/1707.06887
Distributional Reinforcement Learning with Quantile Regression	https://arxiv.org/abs/1710.10044
The Option-Critic Architecture	https://arxiv.org/abs/1609.05140
Addressing Function Approximation Error in Actor-Critic Methods	https://arxiv.org/abs/1802.09477
DeepMind Control Suite	https://arxiv.org/abs/1801.00690
OpenAI Baselines	https://github.com/openai/baselines
Ilya Kostrikov	https://github.com/ikostrikov/pytorch-a2c-ppo-acktr
	https://github.com/binaryknight/DeepRL#code-of-my-papers
Generalized Off-Policy Actor-Critic	https://arxiv.org/abs/1903.11329
Geoff-PAC	https://github.com/ShangtongZhang/DeepRL/tree/Geoff-PAC
TD3-random	https://github.com/ShangtongZhang/DeepRL/tree/TD3-random
DAC: The Double Actor-Critic Architecture for Learning Options	https://arxiv.org/abs/1904.12691
DAC	https://github.com/ShangtongZhang/DeepRL/tree/DAC
QUOTA: The Quantile Option Architecture for Reinforcement Learning	https://arxiv.org/abs/1811.02073
QUOTA-discrete	https://github.com/ShangtongZhang/DeepRL/tree/QUOTA-discrete
QUOTA-continuous	https://github.com/ShangtongZhang/DeepRL/tree/QUOTA-continuous
ACE: An Actor Ensemble Algorithm for Continuous Control with Tree Search	https://arxiv.org/abs/1811.02696
ACE	https://github.com/ShangtongZhang/DeepRL/tree/ACE
Readme	https://github.com/binaryknight/DeepRL#readme-ov-file
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