OpenAI Gym's LunarLander-v2 Implementation

If you are into Reinforcement Learning, it's very likely that you've heard about OpenAI Gym. It's an amazing platform that you should check out in case you haven't heard about it.

This post is specifically about the LunarLander-v2 environment and my implementation to solve it. This environment consists of a lander that, by learning how to control 4 different actions, has to land safely on a landing pad with both legs touching the ground.

This was my first exciting Reinforcement Learning problem and I'm very proud of the work I did and everything I learned in the process. Here are some cool things I got to use while working on this project:

  • Deep Q-Network (DQN)
  • Deep Neural Networks (DNN)
  • Experience Replay

Most than anything, this project got me to love Reinforcement Learning and helped me understand the power of it.

Here is the link to the GitHub repo with my solution that also includes the full analysis.

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