Lectures on Data Science:

HDS-LEE Hackathon „Hearts Gym” 2024

Monday, 13.05. - Wednesday, 15.05.2024 · 9 a.m. - 5 p.m.

Hearts Gym Hackathon 2024

About the Hackathon

Learning reinforcement learning in a card game: Reinforcement learning is used to teach an agent optimal strategies (policy) to achieve maximum reward in a Markov decision process by using a simple card game: Hearts. In Hearts, four players play against each other and have to avoid winning hands that include hearts or the queen of spades. These players can be modelled as reinforcement learning agents. The Helmholtz AI team at FZJ created a multi-agent environment to train agents on playing the Hearts game, which also includes a client-server architecture to remotely evaluate local agents: https://github.com/HelmholtzAI-FZJ/hearts-gym. In this server architecture, the agents can battle against each other to evaluate which group has taught the best cards player. The overall aim is to do some Collaborative Coding within the HDS-LEE PhD student community as a networking event.   

Publication: https://arxiv.org/abs/2209.05466


Jan Ebert and Stefan Kesselheim from Helmholtz AI team at FZJ


Basic knowledge in machine learning (ML) and Python programming skills.

Install Python ≥ 3.6, < 3.9 and Git on your system.


Size: 3–5 people

The groups should consists of at least one PhD with good knowledge in ML and one in Python. The group members can either find themselves or are drawn by lot according to these criteria.