Work done at this research meeting has contributed to the creation of the projects

• Approximation, Abstraction and Apartness in Automata Learning (APPLE),
• Trustworthy Analysis of Stochastic Timed Systems (TruSTy), and
• Data-Driven Verification and Learning Under Uncertainty (DEUCE).

This research retreat has the objective to foster collaboration between a number of different universities, namely RWTH Aachen University, University of Saarbruecken, Twente University, and Radboud University Nijmegen. The individual researchers all specialize on aspects related to uncertainty in artificial intelligence, with a desire to render intelligent decision-making in the real world more reliable. The discussed topics will range from theoretical foundations of quantitative programming languages, over formal verification, to state-of-the-art machine learning techniques like deep reinforcement learning.