Current Projects

Abstract Forward Models for Modern Games


This project aims to provide the games industry with access to the latest and most proficient Game AI methods. Statistical Forward Planning (SFP) techniques, such as Monte Carlo Tree Search (MCTS) or Rolling Horizon Evolutionary Algorithms (RHEA), have recently achieved remarkable performance in games research. This project addresses the main reasons behind the small uptake of SFP methods in the games industry: the lack of fast and reliable Forward Models (FM) that can be abstracted for its use by SFP algorithms in modern video-games. SFP needs an FM to work, but complex models are expensive to use without introducing abstractions or simplifications, which also make the model inaccurate.

Hearthstone AI

International Research Competition


I am the organiser of the international research competition on Hearthstone AI, which was part of the IEEE Conference on Computational Intelligence and Games 2018-2020. The competition focuses on the development of autonomous Hearthstone agents and tested the agent’s skill on multiple game playing tasks.

Competition Web-page

Energieoptimale Regelung eines brennstoffgeführten Kraftwerks unter schnell variierenden Randbedingungen

Research Project in Cooperation with University Bremen and Salzgitter AG


In the context of complex industrial processes, coupling gases, which are a byproduct of the production process, can be used to avoid voltage peaks and ensure a reduction in total energy costs. The power plants task is the maximum possible utilisation of the coupling gas, the minimum use of external fuels, the provision of process steam in line with demand and the capping of electrical power peaks by burning leftover coupling gas. The mentioned goals are contradictory and can only be achieved to a certain extent with the help of manual control interventions. In particular, the inaccurate prognosis of consumer behaviour often leads to increased use of foreign fuels. The project’s objective is the development of an automatic control system, which will ensure that the power plant is robust and reliable despite rapidly varying boundary conditions.