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Research Meeting 26303

Challenges in Robust Decision-Making Under Uncertainty

( Jul 22 – Jul 24, 2026 )

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Please use the following short url to reference this page: https://www.dagstuhl.de/26303

Organizers
  • Milan Ceska (Brno University of Technology, CZ)
  • Clemens Dubslaff (TU Eindhoven, NL)
  • Nils Jansen (Ruhr-Universität Bochum, DE)
  • Maximilian Weininger (Ruhr-Universität Bochum, DE)

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Description

This research meeting focuses on a specific branch of Artificial Intelligence, namely decision-making under uncertainty. Specifically, potentially unknown or unpredictable environments, contextual changes at runtime, or incompleteness of data are commonly referred to as uncertainty. Markov Decision Processes (MDPs) are the standard formal model to capture such sequential decision-making problems for systems operating in uncertain environments. However, many real-world problems such as sensor limitations, neural network perception, incomplete data, or causal effects are understudied for these models. In this meeting, we will identify challenges that bring research on decision-making under uncertainty closer to real-world impact.

Copyright Milan Ceska, Clemens Dubslaff, Nils Jansen, and Maximilian Weininger