Post

Air Hockey with Reinforcement Learning

Posted Updated
Results of the Traffic Light Detection model on a batch of images.
Results of the Traffic Light Detection model on a batch of images.
By Magnus Kaut 1 min read

As part of the course “Reinforcement Learning” at the University of Tübingen, I have implemented an agent for the Air Hockey environment using Pygame and OpenAI Gym. The environment simulates a simple air hockey game where an agent controls a paddle to hit a puck towards the opponent’s goal while defending its own goal.

I implemented and trained an agent using the TD3 (Twin Delayed Deep Deterministic Policy Gradient) algorithm, which then took part in the final competition of the course against other students’ agents.

University, Reinforcement Learning
Machine Learning Deep Learning Reinforcement Learning Pygame Python PyTorch OpenAI Gym
This post is licensed under CC BY 4.0 by the author.