Reinforcement learning is a branch of AI that involves training an agent to make optimal decisions in an environment by learning from feedback in the form of rewards or punishments 🧠💪. The agent explores the environment and takes actions to maximize its cumulative reward over time 🚀🎲. Reinforcement learning has practical applications in areas with delayed reward: e.g. robotics 🤖, game playing 🎮, scheduling and logistics. It is a powerful tool for developing intelligent systems that can learn and adapt to complex environments 🤖📈.
Search for TODO text in the repository with CTRL+F and replace it with you code written according to it.
- Clone repository: git clone:
git clone <repository url>
- Complete TODOS the exercises
- Commit your changes
git add <path to the changed files> git commit -m <commit message>
- Push changes to your repository main branch
git push -u origin master
The rest will be taken care of automatically. You can check the GRADE.md file for your grade / test results. Be aware that it may take some time (up to one hour) till this file
Install the requirements
pip install -r requirements.txtRun one of the files from src/benchmarks.
Fox example:
PYTHONPATH=src python src/benchmarks/1-bandits.py