18 citations · 39 across the 17 of their papers we have counts for
8 papers · 1 filter
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…
Benchmarking Surrogate-Assisted Genetic Recommender Systems
Thomas Gabor, Philipp Altmann
We propose a new approach for building recommender systems by adapting surrogate-assisted interactive genetic algorithms. A pool of user-evaluated items is used to construct an app…
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…
A Quantum Annealing Algorithm for Finding Pure Nash Equilibria in Graphical Games
Christoph Roch, Thomy Phan, Sebastian Feld +3
We introduce Q-Nash, a quantum annealing algorithm for the NP-complete problem of Fnding pure Nash equilibria in graphical games. The algorithm consists of two phases. The first ph…
Assessing Solution Quality of 3SAT on a Quantum Annealing Platform
Thomas Gabor, Sebastian Zielinski, Sebastian Feld +6
When solving propositional logic satisfiability (specifically 3SAT) using quantum annealing, we analyze the effect the difficulty of different instances of the problem has on the q…
Adapting Quality Assurance to Adaptive Systems: The Scenario Coevolution Paradigm
Thomas Gabor, Marie Kiermeier, Andreas Sedlmeier +5
From formal and practical analysis, we identify new challenges that self-adaptive systems pose to the process of quality assurance. When tackling these, the effort spent on various…