Reinforcement Learning for Digital Business

Welcome to the "Reinforcement Learning for Digital Business" repository! This project provides simple implementations of reinforcement learning algorithms for online advertising and inventory management in a simulated environment. Follow the steps below to get started.

Getting Started

Step 1: Set up the Environment

1. Create a virtual environment using Conda:
   Note: This environment tested with python version 3.7, so if you need to reproduce this code without problem, please use same python version.

   conda create --name rl4db python=3.7

2. Activate the virtual environment:

   conda activate rl4db

Step 2: Install Requirements

Install the required Python packages by running:

pip install -r requirements.txt

Note: If you encounter the error AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline', reinstall opencv-python-headless using pip:

pip uninstall opencv-python-headless
pip install opencv-python-headless

Running the Examples

Explore the provided examples for reinforcement learning in online advertising and inventory management. Each example is located in its respective directory.