This repository provides a collection of reinforcement learning algorithms implemented in Python using TensorFlow. It aims to be highly readable and easy to understand, targeting learners and researchers who want to explore and implement various RL techniques.

How It Works

The project emphasizes readability and simplicity, utilizing Python and the high-level TensorFlow API. Algorithms are organized into categories based on a file naming convention (e.g., 07_ for DQN, 08_ for Policy Gradient), with descriptions indicating the file's purpose. This approach facilitates learning and debugging by keeping the code clean and understandable.

Quick Start & Requirements

• Install requirements: pip install -r requirements.txt
• Run tests and auto-formatting: pytest and autopep8 . --recursive --in-place --pep8-passes 2000 --verbose --ignore E501
• Prerequisites: Python, TensorFlow, OpenAI Gym.

Highlighted Details

• Algorithms categorized by file naming convention (e.g., 07_ for DQN, 08_ for Policy Gradient).
• Includes a gym_uploader.py script for uploading results to OpenAI Gym.
• Emphasis on PEP8 compliance and docstrings for code readability.

Maintenance & Community

This is a work in progress, and the project actively calls for comments and pull requests.

Licensing & Compatibility

The repository does not explicitly state a license.

Limitations & Caveats

The project is explicitly stated as a work in progress and may contain bugs. There is no explicit mention of supported environments or tested compatibility.