Projects available for MSc thesis and interships.


  • Sensitivity-guided Exploration for Learning Markov Chains
    Mees Meuwissen
  • Robust Permisive Policies for Interval Markov Decision Processes
    Bram Pellen
  • Verifying Inter-Process Communication Between ASML Components
    Renato Feroce
  • Improving Deep Q-Learning Performance through Imitation Learning
    Bas Neeleman
  • Card Games as Constrained Reinforcement Learning Problem
    Michel van Wijk


2023 Active Measuring in Uncertain Environments
Merlijn Krale
Online Planning in Many-Agent POMDPs Addressing Scaling Issues
Maris Galesloot
The Underlying Belief Model of Uncertain Partially Observable Markov Decision Processes
Eline Bovy
Safe Reinforcement Learning From Pixel Observations Using a Stochastic Latent Actor-Critic
Yannick Hogewind
2022 Optimal Order Execution for FX trading
Pleun Koldewijn
2021 Model Learning of Deterministic MDPs
Marck van der Vegt
History-based Rewards for POMDPs
Serena Rietbergen
Optimal Maintenance Strategies for an Industrial Scrubber System
Ilse Pool
Evaluating Adversarial Attack Detectors using Formal Verification Methods
Reinier Joosse
Grouping of Maintenance Actions on Sewer Pipes: Using Deep Reinforcement Learning and Graph Neural Networks
David Kerkkamp
Formal Verification in Uncertain POMDPs
Nils Neerhof
2020 Approximating Black-Box Deep Neural Networks using Active Learning as a Proxy Measurement for Robustness
Christoph Schmidl
Entropy-guided decision making in multiple-environment Markov decision processes
Marnix Suilen