Daniel Lütticke

18 papers Journal 6Unranked 12
YearRankTypeTitle / Venue / Authors
2024 J jnl
A Data-Driven Two-Phase Multi-Split Causal Ensemble Model for Time Series.
CoRR
Zhipeng Ma, Marco Kemmerling, Daniel Buschmann, Chrismarie Enslin, Daniel Lütticke, Robert H. Schmitt
2024 J jnl
Beyond games: a systematic review of neural Monte Carlo tree search applications.
Appl. Intell.
Marco Kemmerling, Daniel Lütticke, Robert H. Schmitt
2023 J jnl
A Data-Driven Two-Phase Multi-Split Causal Ensemble Model for Time Series.
Symmetry
Zhipeng Ma, Marco Kemmerling, Daniel Buschmann, Chrismarie Enslin, Daniel Lütticke, Robert H. Schmitt
2023 J jnl
Beyond Games: A Systematic Review of Neural Monte Carlo Tree Search Applications.
CoRR
Marco Kemmerling, Daniel Lütticke, Robert H. Schmitt
2023 J jnl
Evolving the Digital Industrial Infrastructure for Production: Steps Taken and the Road Ahead.
CoRR
Jan Pennekamp, Anastasiia Belova, Thomas Bergs, Matthias Bodenbenner, Andreas Bührig-Polaczek, Markus Dahlmanns, Ike Kunze, Moritz Kröger, Sandra Geisler, Martin Henze, Daniel Lütticke, Benjamin Montavon, Philipp Niemietz, Lucia Ortjohann, Maximilian Rudack, Robert H. Schmitt, Uwe Vroomen, Klaus Wehrle, Michael Zeng
2023 — conf
Human-Machine Learning Approach for Ejection System Design in Injection Molds.
HCI (41)
Johanna Lauwigi, Robert Jungnickel, Daniel Lütticke
2023 — conf
Reward Shaping for Job Shop Scheduling.
LOD (1)
Alexander Nasuta, Marco Kemmerling, Daniel Lütticke, Robert H. Schmitt
2022 — conf
A Conceptual Framework for Production Process Parameter Optimization with Modular Hybrid Simulations.
SEFM Workshops
Sylwia Olbrych, Marco Kemmerling, Hans Aoyang Zhou, Daniel Lütticke, Robert H. Schmitt
2022 — conf
Controlled Synthesis of Fibre-reinforced Plastics Images from Segmentation Maps using Generative Adversarial Neural Networks.
ICAART (3)
Nicolas Schaaf, Hans Aoyang Zhou, Chrismarie Enslin, Florian Brillowski, Daniel Lütticke
2022 J jnl
Deep Reinforcement Learning for Robotic Control in High-Dexterity Assembly Tasks - A Reward Curriculum Approach.
Int. J. Semantic Comput.
Lars Leyendecker, Markus Schmitz, Hans Aoyang Zhou, Vladimir Samsonov, Marius Rittstieg, Daniel Lütticke
2022 — conf
Human-Centric Machine Learning Approach for Injection Mold Design: Towards Automated Ejector Pin Placement.
LOD (2)
Robert Jungnickel, Johanna Lauwigi, Vladimir Samsonov, Daniel Lütticke
2021 — conf
Deep Reinforcement Learning for Robotic Control in High-Dexterity Assembly Tasks - A Reward Curriculum Approach.
IRC
Lars Leyendecker, Markus Schmitz, Hans Aoyang Zhou, Vladimir Samsonov, Marius Rittstieg, Daniel Lütticke
2021 — conf
Digitizing a Distributed Textile Production Process using Industrial Internet of Things: A Use-Case.
ICPS
Michael Rath, Aymen Gannouni, Daniel Lütticke, Thomas Gries
2021 — conf
Manufacturing Control in Job Shop Environments with Reinforcement Learning.
ICAART (2)
Vladimir Samsonov, Marco Kemmerling, Maren Paegert, Daniel Lütticke, Frederick Sauermann, Andreas Gützlaff, Günther Schuh, Tobias Meisen
2021 — conf
Optimisation of a Workpiece Clamping Position with Reinforcement Learning for Complex Milling Applications.
LOD
Chrismarie Enslin, Vladimir Samsonov, Hans-Georg Köpken, Schirin Bär, Daniel Lütticke
2020 — conf
Using Reinforcement Learning for Optimization of a Workpiece Clamping Position in a Machine Tool.
ICEIS (1)
Vladimir Samsonov, Chrismarie Enslin, Hans-Georg Köpken, Schirin Baer, Daniel Lütticke
2018 — conf
Design of an Automated Measuring System for RFID Transponders in Complex Environments.
RFID-TA
Daniel Lütticke, Tobias Meisen
2017 — conf
Cyber-Physical Production Systems: A Teaching Concept in Engineering Education.
IIAI-AAI
Daniela Antkowiak, Daniel Lütticke, Tristan Langer, Thomas Thiele, Tobias Meisen, Sabina Jeschke