https://github.com/thirdeyeinfo/lunar-lander

Lunar Lander training using Deep-Q-Learning
https://github.com/thirdeyeinfo/lunar-lander

artificial-intelligence deep-q-learning deep-q-network experience-replay gymnasium

Last synced: about 2 months ago
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Lunar Lander training using Deep-Q-Learning

• Host: GitHub
• URL: https://github.com/thirdeyeinfo/lunar-lander
• Owner: ThirdEyeInfo
• License: mit
• Created: 2024-04-14T06:00:39.000Z (9 months ago)
• Default Branch: main
• Last Pushed: 2024-04-19T10:25:12.000Z (9 months ago)
• Last Synced: 2024-04-19T11:38:55.767Z (9 months ago)
• Topics: artificial-intelligence, deep-q-learning, deep-q-network, experience-replay, gymnasium
• Language: Python
• Homepage: https://colab.research.google.com/drive/1SgdMlL2zM2HERCBJ5yhpVtbO7QtdDGMh#scrollTo=2ybZW6Im-Bwj
• Size: 31.3 KB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
## Step to train Lunar Lander model

- Clone lunar-lander in your local machine

- Download and install Anaconda from https://www.anaconda.com/download

- Type anaconda on windows search and open anaconda command prompt

- Navigate to lunar-lander progect (in step 1) from conda prompt and/by follow below commands

    * cd /lunar-lander

    * conda create -n lunar-lander python=3.11 -y

    * conda activate lunar-lander

    * conda install swig -y

    * pip install -r requirements.txt

    * python setup.py install

- Run below python command to train your Lunar Module and generate video.mp4

    * python render.py

![image](https://github.com/ThirdEyeInfo/lunar-lander/assets/93641638/b8000816-ddf1-46c3-8c1d-e853bff4291c)

- Find video.mp4 under lunar-lander folder, play it to witness the landing of Lunar Lander as shown in below

![image](https://github.com/ThirdEyeInfo/lunar-lander/assets/93641638/c26a9152-3a7e-4a4a-aa5e-b4771ba795b5)