https://github.com/justinvalentine/reinforcement-learning-workshop-2022
Workshop held at UofA through the UAIS
https://github.com/justinvalentine/reinforcement-learning-workshop-2022
openai-gym qlearning reinforcement-learning workflow
Last synced: about 2 months ago
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Workshop held at UofA through the UAIS
- Host: GitHub
- URL: https://github.com/justinvalentine/reinforcement-learning-workshop-2022
- Owner: JustinValentine
- Created: 2022-10-29T07:41:44.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2022-11-04T20:53:28.000Z (over 3 years ago)
- Last Synced: 2025-04-09T06:18:33.345Z (about 1 year ago)
- Topics: openai-gym, qlearning, reinforcement-learning, workflow
- Language: Python
- Homepage:
- Size: 25.9 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Reinforcement-Learning-Workshop-2022
The accompanying slides are [here](https://docs.google.com/presentation/d/1mvGdp7hg0sJhwTD7Dr4b7YCOmsuGGPXnZuCEL-GLZZY/edit#slide=id.p)
In this demo will be using [OpenAi Gym](https://www.gymlibrary.dev/), a standard API for reinforcement learning with a lot of built in environments
# Installation & Setup
### Setting up the virtual envorment
#### Using Conda
- 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`
- Next we will active our enviorment `conda activate uais-rl`
- If you do not have miniconda installed you can get it [here](https://docs.conda.io/en/latest/miniconda.html)
#### Using venv
- 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`
- To activate on **Windows** run: `OpenAiGym-env\Scripts\activate.bat`
- To activate on **Unix or MacOS** run: `source OpenAiGym-env/bin/activate`
### Setting up the virtual enviorment kernel for Jupyter Notebook
- Firstly lets install Jupyter Notebook `pip install notebook`
- First we need to install the following package `pip install --user ipykernel`
- Next we need to add the kernel so we can have it in our Jupyter Notebook `python -m ipykernel install --user --name=uais-rl`
- Later if you wanna remove the enverment use `jupyter kernelspec uninstall myenv`
### Installation - Notebook Only
- Next we need to install the base gym library `pip install gym`
- We will also need to install the atari enviorment dependences `pip install 'gym[atari]'`
- 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
- Next we will use ALE to import our ROM `ale-import-roms ROMS/`
- Next install imageio for capturing our image frames `pip install imageio`
- and lastly install cv2 `pip install opencv-python`
### Installation - Deep Reinforcement Learning
- Next install pytorch `conda install pytorch -c pytorch`
- Next clone [this](https://github.com/facebookresearch/torchbeast) repo
- and then install all the requirements `pip install -r requirements.txt`
- lastly `pip install 'stable-baselines3[extra]'`
### More info
- A good artical to help you get started with OpenAi Gym is [here](https://blog.paperspace.com/getting-started-with-openai-gym/)
- 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)