• Efficient Reinforcement Learning Algorithms
• Intelligent Robot Control Architectures
• Learning in Multiagent Systems
• Supervised and Unsupervised Learning Methods
• Autonomous Robots: Robotic Soccer and beyond
• (Industrial) Applications
• Machine Learning for Games

For the full list of projects follow this link.

Pacman vs. Ghosts

The Ms. Pac-Man vs. Ghosts Competition provides an easy and fun way for students to experiment with different Machine Learning techniques in order to beat this arcade classic. Several groups of our students tried their wits on this competition, with approaches ranging from simple solvers to Neuro-Evolution. Read more...

Brainstormers Tribots

Robotic soccer is an ideal testbed for our vision of learning and adaptive mobile robots. The challenges are manifold: uncertainty in sensors and actuators, complex and nonlinear kinematics and dynamics, huge state space, hostile robots and the need for team cooperation with other robots. Read more...

Brainstormers 2D

Robotic soccer is an ideal testbed for our vision of learning and adaptive computer programs. The Brainstormers robotic soccer project was established in 1998, starting with a team competing in the soccer simulation league. Read more...

CLSquare: Closed Loop Simulation System

Download our Open Source Closed Loop Simulation System CLS2 for training and testing your learning controller. Version 4.0 is now available and includes new ready-to use RL-controllers. Read more...

Memory Consolidation in Learning Robots

In this project, we are focusing on a new architecture for memory-based RL. This architecture has two main features: a filtering mechanism for a more efficient use of memory based learning by focusing on relevant data as well as a short term memory containing the recent history of the agent in a condensed form to guide decision making. Read more...

Sales Rate Prediction and Automatic Disposition

In this joint project with the Axel-Springer-Verlag, we develop a system based on machine learning techniques aimed at predicting the daily sales rates of newspapers. The task comprises forecasting thousands of timeseries for individual sales agents differing in many facets like the average sales level, the noise ratio, seasonal changes, and individual characteristics of the respective retailer. Read more...

More projects can be found in the complete list of projects.