This project is a simple implementation of the Multi-Armed Bandit problem. The Multi-Armed Bandit problem is a classic problem in reinforcement learning where an agent has to choose between multiple actions, each with an unknown reward. The agent has to learn which action is the best to maximize its reward. In this project, we implement the epsilon-greedy algorithm to solve the Multi-Armed Bandit problem.
To install the project, you can clone the repository and install the required dependencies using the following commands:
git clone
cd project-bandits
pip install -r requirements.txt