{"id":25368515,"url":"https://github.com/justinvalentine/reinforcement-learning-workshop-2022","last_synced_at":"2026-05-01T19:34:34.579Z","repository":{"id":62297993,"uuid":"559145799","full_name":"JustinValentine/Reinforcement-Learning-Workshop-2022","owner":"JustinValentine","description":"Workshop held at UofA through the 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Reinforcement-Learning-Workshop-2022\nThe accompanying slides are [here](https://docs.google.com/presentation/d/1mvGdp7hg0sJhwTD7Dr4b7YCOmsuGGPXnZuCEL-GLZZY/edit#slide=id.p)\n\nIn this demo will be using [OpenAi Gym](https://www.gymlibrary.dev/), a standard API for reinforcement learning with a lot of built in environments\n\n# Installation \u0026 Setup\n### Setting up the virtual envorment \n#### Using Conda \n- Lets create a new virtual enviorment to house our new project called **OpenAiGym** by typing the following comand into the terminal `conda create -n uais-rl python=3.7`\n- Next we will active our enviorment `conda activate uais-rl`\n- If you do not have miniconda installed you can get it [here](https://docs.conda.io/en/latest/miniconda.html) \n\n#### Using venv\n- Lets create a new virtual enviorment to house our new project called **OpenAiGym** by typing the following comand into the terminal `python3 -m venv OpenAiGym-env`\n- To activate on **Windows** run: `OpenAiGym-env\\Scripts\\activate.bat`\n- To activate on **Unix or MacOS** run: `source OpenAiGym-env/bin/activate`\n\n### Setting up the virtual enviorment kernel for Jupyter Notebook\n- Firstly lets install Jupyter Notebook `pip install notebook`\n- First we need to install the following package `pip install --user ipykernel`\n- Next we need to add the kernel so we can have it in our Jupyter Notebook `python -m ipykernel install --user --name=uais-rl`\n- Later if you wanna remove the enverment use `jupyter kernelspec uninstall myenv`\n\n### Installation - Notebook Only \n- Next we need to install the base gym library `pip install gym` \n- We will  also need to install the atari enviorment dependences `pip install 'gym[atari]'`\n- You can freely download Atari 2600 roms [here](http://www.atarimania.com/rom_collection_archive_atari_2600_roms.html) but the Breakout ROM that we will be using is provided \n- Next we will use ALE to import our ROM `ale-import-roms ROMS/`\n- Next install imageio for capturing our image frames `pip install imageio`\n- and lastly install cv2 `pip install opencv-python`\n### Installation - Deep Reinforcement Learning \n- Next install pytorch `conda install pytorch -c pytorch`\n- Next clone [this](https://github.com/facebookresearch/torchbeast) repo\n- and then install all the requirements `pip install -r requirements.txt`\n- lastly `pip install 'stable-baselines3[extra]'` \n\n### More info\n- A good artical to help you get started with OpenAi Gym is [here](https://blog.paperspace.com/getting-started-with-openai-gym/)\n- Another article that was very helpful for setting up the Atari environment is [here](https://blog.devgenius.io/teaching-a-neural-network-to-play-the-breakout-game-793ad7d1b20e)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjustinvalentine%2Freinforcement-learning-workshop-2022","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjustinvalentine%2Freinforcement-learning-workshop-2022","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjustinvalentine%2Freinforcement-learning-workshop-2022/lists"}