In the morning, we will introduce the main reinforcement learning approaches. Participants will get familiar with them by solving toy problems.

In the afternoon, participants will design their own agent, which will then interact with other people’s agents in a (friendly) competitive setting.

Participants will discover what reinforcement learning is, what it can do, and what are its current limitations and perspectives. They will get hands-on experience by building and tweaking agents in a competitive setting. 

• Each participant is expected to actively take part by designing and training RL agents on their machine.
• Participants can also form small teams, working on the same laptop on a single agent.
• A recent laptop is recommended, but a GPU is not required.
• Participants should have a good knowledge of Python, and at least a basic understanding of machine learning.
• No knowledge of reinforcement learning is expected. We will use the PyTorch framework, but we don’t expect participants to be familiar with it.