/Reinforcement_Learning

Reinforcement learning tutorials

Primary LanguagePythonMIT LicenseMIT

Reinforcement Learning Tutorials:

2020-10-07 added support for Tensorflow 2.3.1

PPO and PPO_CNN agents playing Pong-v0 game:
PPO agent PPO CNN agent

2020-10-10 added LunarLander-v2_PPO Continuous code for Tensorflow 2.3.1: LunarLander-v2_PPO

2020-10-23 added BipedalWalker-v3_PPO code for Tensorflow 2.3.1: BipedalWalker-v3_PPO_PPO

  1. Deep Q Learning tutorial (DQN)

  2. Double Deep Q Learning tutorial (DDQN)

  3. Dueling Double Deep Q Learning tutorial (D3QN)

  4. Epsilon Greedy Dueling Double Deep Q Learning tutorial (D3QN)

  5. Prioritized Experience Replay (PER) D3QN tutorial

  6. D3QN PER with Convolutional Neural Networks tutorial

  7. A.I. learns to play Pong with DQN

  8. Introduction to RL Policy Gradient (PG or REINFORCE)

  9. Introduction to RL Advanced Actor Critic algorythm (A2C)

  10. Introduction to RL Asynchronous Advanced Actor Critic algorythm (A3C)

  11. Introduction to RL Proximal Policy Optimization algorythm (PPO)

  12. Let’s code from scratch a discrete Reinforcement Learning rocket landing agent! (PPO)

  13. Continuous Proximal Policy Optimization Tutorial with OpenAI gym environment! (PPO)

    PPO Pong-v0 Learning curve: