3 citations · 9 across the 10 of their papers we have counts for
15 papers
Synthesizing Safe Policies under Probabilistic Constraints with Reinforcement Learning and Bayesian Model Checking
Lenz Belzner, Martin Wirsing
We propose to leverage epistemic uncertainty about constraint satisfaction of a reinforcement learner in safety critical domains. We introduce a framework for specification of requ…
The Holy Grail of Quantum Artificial Intelligence: Major Challenges in Accelerating the Machine Learning Pipeline
Thomas Gabor, Leo Sünkel, Fabian Ritz +5
We discuss the synergetic connection between quantum computing and artificial intelligence. After surveying current approaches to quantum artificial intelligence and relating them…
Trajectory annotation using sequences of spatial perception
Sebastian Feld, Steffen Illium, Andreas Sedlmeier +1
In the near future, more and more machines will perform tasks in the vicinity of human spaces or support them directly in their spatially bound activities. In order to simplify the…
Bayesian Surprise in Indoor Environments
Sebastian Feld, Andreas Sedlmeier, Markus Friedrich +2
This paper proposes a novel method to identify unexpected structures in 2D floor plans using the concept of Bayesian Surprise. Taking into account that a person's expectation is an…
Uncertainty-Based Out-of-Distribution Classification in Deep Reinforcement Learning
Andreas Sedlmeier, Thomas Gabor, Thomy Phan +2
Robustness to out-of-distribution (OOD) data is an important goal in building reliable machine learning systems. Especially in autonomous systems, wrong predictions for OOD inputs…
Emergent Escape-based Flocking Behavior using Multi-Agent Reinforcement Learning
Carsten Hahn, Thomy Phan, Thomas Gabor +2
In nature, flocking or swarm behavior is observed in many species as it has beneficial properties like reducing the probability of being caught by a predator. In this paper, we pro…