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Reinforcement Learning Methods and Tutorials

In these tutorials for reinforcement learning, it covers from the basic RL algorithms to advanced algorithms developed recent years.

If you speak Chinese, visit 莫烦 Python or my Youtube channel for more.

As many requests about making these tutorials available in English, please find them in this playlist: (https://www.youtube.com/playlist?list=PLXO45tsB95cIplu-fLMpUEEZTwrDNh6Ba)

Table of Contents

Some RL Networks

Deep Q Network

Double DQN

Dueling DQN

Actor Critic

Deep Deterministic Policy Gradient

A3C

Proximal Policy Optimization (PPO)

Curiosity Model

Donation

If this does help you, please consider donating to support me for better tutorials. Any contribution is greatly appreciated!

Paypal

Patreon

Core symbols most depended-on inside this repo

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Method 321
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Function 21

Languages

Python100%

Modules by API surface

experiments/Solve_BipedalWalker/DDPG.py25 symbols
experiments/Solve_LunarLander/DuelingDQNPrioritizedReplay.py22 symbols
experiments/Robot_arm/arm_env.py18 symbols
contents/5.2_Prioritized_Replay_DQN/RL_brain.py18 symbols
experiments/Robot_arm/DDPG.py16 symbols
experiments/2D_car/DDPG.py16 symbols
experiments/2D_car/car_env.py14 symbols
contents/9_Deep_Deterministic_Policy_Gradient_DDPG/DDPG.py14 symbols
contents/3_Sarsa_maze/RL_brain.py11 symbols
contents/11_Dyna_Q/RL_brain.py10 symbols
experiments/Solve_LunarLander/A3C.py9 symbols
experiments/Solve_BipedalWalker/A3C_rnn.py9 symbols

For agents

$ claude mcp add Reinforcement-learning-with-tensorflow \
  -- python -m otcore.mcp_server <graph>

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