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Title: GitHub - akashe/DeepReinforcementLearning: Deep RL implementations. DQN, SAC, DDPG, TD3, PPO and VPG implemented in pytorch. Tested Env: LunarLander-v2 and Pendulum-v0. · GitHub

Open Graph Title: GitHub - akashe/DeepReinforcementLearning: Deep RL implementations. DQN, SAC, DDPG, TD3, PPO and VPG implemented in pytorch. Tested Env: LunarLander-v2 and Pendulum-v0.

X Title: GitHub - akashe/DeepReinforcementLearning: Deep RL implementations. DQN, SAC, DDPG, TD3, PPO and VPG implemented in pytorch. Tested Env: LunarLander-v2 and Pendulum-v0.

Description: Deep RL implementations. DQN, SAC, DDPG, TD3, PPO and VPG implemented in pytorch. Tested Env: LunarLander-v2 and Pendulum-v0. - akashe/DeepReinforcementLearning

Open Graph Description: Deep RL implementations. DQN, SAC, DDPG, TD3, PPO and VPG implemented in pytorch. Tested Env: LunarLander-v2 and Pendulum-v0. - akashe/DeepReinforcementLearning

X Description: Deep RL implementations. DQN, SAC, DDPG, TD3, PPO and VPG implemented in pytorch. Tested Env: LunarLander-v2 and Pendulum-v0. - akashe/DeepReinforcementLearning

Opengraph URL: https://github.com/akashe/DeepReinforcementLearning

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README	https://github.com/akashe/DeepReinforcementLearning
	https://github.com/akashe/DeepReinforcementLearning#deep-rl-algorithms-implemented-using-pytorch
	https://github.com/akashe/DeepReinforcementLearning#algo-list
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	https://github.com/akashe/DeepReinforcementLearning#article-on-deeper-look-into-policy-gradients
	https://github.com/akashe/DeepReinforcementLearning#experimental-results
	https://raw.githubusercontent.com/akashe/DeepReinforcementLearning/main/figures/DQN_Lunar_lander_rewards.png
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	https://raw.githubusercontent.com/akashe/DeepReinforcementLearning/main/figures/PPO_Pendulum-v0_rewards.png
	https://github.com/akashe/DeepReinforcementLearning#resources
RL course by David Silver	https://www.youtube.com/watch?v=KHZVXao4qXs&list=PLqYmG7hTraZDM-OYHWgPebj2MfCFzFObQ&index=7
Lecture slides for above course	https://www.davidsilver.uk/teaching/
Spinning up by OpenAI	https://spinningup.openai.com
More exhaustive RL guide by Deeny Britz	https://github.com/dennybritz/reinforcement-learning
	https://github.com/akashe/DeepReinforcementLearning#installation
pyenv	https://github.com/pyenv/pyenv
Homebrew	https://brew.sh/
	https://github.com/akashe/DeepReinforcementLearning#usage
akashe.io/blog/2020/10/14/policy-gradient-methods/	https://akashe.io/blog/2020/10/14/policy-gradient-methods/
algorithms	https://github.com/topics/algorithms
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