no code implementations • 19 Oct 2023 • Yannik Hahn, Robert Maack, Guido Buchholz, Marion Purrio, Matthias Angerhausen, Hasan Tercan, Tobias Meisen
The digitization of manufacturing processes enables promising applications for machine learning-assisted quality assurance.
no code implementations • 17 May 2023 • Constantin Waubert de Puiseau, Hasan Tercan, Tobias Meisen
In this paper, we further improve DLR as an underlying method by actively incorporating the variability of difficulty within the same problem size into the design of the learning process.
1 code implementation • 10 Jan 2023 • Constantin Waubert de Puiseau, Jannik Peters, Christian Dörpelkus, Hasan Tercan, Tobias Meisen
Research on deep reinforcement learning (DRL) based production scheduling (PS) has gained a lot of attention in recent years, primarily due to the high demand for optimizing scheduling problems in diverse industry settings.
1 code implementation • 1 Dec 2022 • Christian Bitter, Timo Thun, Tobias Meisen
In reinforcement learning (RL) research, simulations enable benchmarks between algorithms, as well as prototyping and hyper-parameter tuning of agents.
no code implementations • 14 May 2020 • Andreas Burgdorf, André Pomp, Tobias Meisen
Finally, we will use the created ontology and automatically identified semantic models to either rate descriptions for new data sources or even to automatically generate descriptive texts that are easier to understand by the human user than formal models.
no code implementations • 7 Apr 2020 • Richard Meyes, Moritz Schneider, Tobias Meisen
We show that the healthy agent's behavior is characterized by a distinct correlation pattern between the network's layer activation and the performed actions during an episode and that network ablations, which cause a strong change of this pattern, lead to the agent failing its trained control task.
no code implementations • 2 Apr 2020 • Richard Meyes, Constantin Waubert de Puiseau, Andres Posada-Moreno, Tobias Meisen
The need for more transparency of the decision-making processes in artificial neural networks steadily increases driven by their applications in safety critical and ethically challenging domains such as autonomous driving or medical diagnostics.
no code implementations • 7 Aug 2019 • Andrei Ionita, André Pomp, Michael Cochez, Tobias Meisen, Stefan Decker
Smart cities around the world have begun monitoring parking areas in order to estimate available parking spots and help drivers looking for parking.
1 code implementation • 24 Jan 2019 • Richard Meyes, Melanie Lu, Constantin Waubert de Puiseau, Tobias Meisen
considering the growth in size and complexity of state-of-the-art artificial neural networks (ANNs) and the corresponding growth in complexity of the tasks that are tackled by these networks, the question arises whether ablation studies may be used to investigate these networks for a similar organization of their inner representations.
no code implementations • 13 Dec 2018 • Peter E. Lillian, Richard Meyes, Tobias Meisen
It is still not fully understood exactly how neural networks are able to solve the complex tasks that have recently pushed AI research forward.