6 citations · 9 across the 9 of their papers we have counts for
4 papers · 1 filter
Adaptive Probabilistic Shielding by Learning MDPs for Safe Reinforcement Learning
Astrid Horn Brorholt, Maris F. L. Galesloot, Nils Jansen +2
Probabilistic shielding is a technique for safe reinforcement learning (RL). Typically, a static observer -- called the shield -- constrains the learning agent's actions to those f…
Missingness-MDPs: Bridging the Theory of Missing Data and POMDPs
Joshua Wendland, Markel Zubia, Roman Andriushchenko +6
We introduce missingness-MDPs (miss-MDPs), a novel subclass of partially observable Markov decision processes (POMDPs) that incorporates the theory of missing data. A miss-MDP is a…
Robust Probabilistic Shielding for Safe Offline Reinforcement Learning
Maris F. L. Galesloot, Thomas Rhemrev, Nils Jansen
In offline reinforcement learning (RL), we learn policies from fixed datasets without environment interaction. The major challenges are to provide guarantees on the (1) performance…
Perception-Based Beliefs for POMDPs with Visual Observations
Miriam Schäfers, Merlijn Krale, Thiago D. Simão +2
Partially observable Markov decision processes (POMDPs) are a principled planning model for sequential decision-making under uncertainty. Yet, real-world problems with high-dimensi…