Cyber-Physical Production Systems: A Teaching Concept in Engineering Education. - Daniela Antkowiak; Daniel Lütticke; Tristan Langer; Thomas Thiele; Tobias Meisen; Sabina Jeschke (IIAI-AAI, 2017)

Design of an Automated Measuring System for RFID Transponders in Complex Environments. - Daniel Lütticke; Tobias Meisen (RFID-TA, 2018)

Using Reinforcement Learning for Optimization of a Workpiece Clamping Position in a Machine Tool. - Vladimir Samsonov; Chrismarie Enslin; Hans-Georg Köpken; Schirin Baer; Daniel Lütticke (ICEIS (1), 2020)

Manufacturing Control in Job Shop Environments with Reinforcement Learning. - Vladimir Samsonov; Marco Kemmerling; Maren Paegert; Daniel Lütticke; Frederick Sauermann; Andreas Gützlaff; Günther Schuh; Tobias Meisen (ICAART (2), 2021)

Digitizing a Distributed Textile Production Process using Industrial Internet of Things: A Use-Case. - Michael Rath 003; Aymen Gannouni; Daniel Lütticke; Thomas Gries (ICPS, 2021)

Optimisation of a Workpiece Clamping Position with Reinforcement Learning for Complex Milling Applications. - Chrismarie Enslin; Vladimir Samsonov; Hans-Georg Köpken; Schirin Bär; Daniel Lütticke (LOD, 2021)

Controlled Synthesis of Fibre-reinforced Plastics Images from Segmentation Maps using Generative Adversarial Neural Networks. - Nicolas Schaaf; Hans Aoyang Zhou; Chrismarie Enslin; Florian Brillowski; Daniel Lütticke (ICAART (3), 2022)

Human-Centric Machine Learning Approach for Injection Mold Design: Towards Automated Ejector Pin Placement. - Robert Jungnickel; Johanna Lauwigi; Vladimir Samsonov; Daniel Lütticke (LOD (2), 2022)

A Conceptual Framework for Production Process Parameter Optimization with Modular Hybrid Simulations. - Sylwia Olbrych; Marco Kemmerling; Hans Aoyang Zhou; Daniel Lütticke; Robert H. Schmitt (SEFM Workshops, 2022)

Deep Reinforcement Learning for Robotic Control in High-Dexterity Assembly Tasks - A Reward Curriculum Approach. - Lars Leyendecker; Markus Schmitz; Hans Aoyang Zhou; Vladimir Samsonov; Marius Rittstieg; Daniel Lütticke (Int. J. Semantic Comput., 2022)

Human-Machine Learning Approach for Ejection System Design in Injection Molds. - Johanna Lauwigi; Robert Jungnickel; Daniel Lütticke (HCI (41), 2023)

Reward Shaping for Job Shop Scheduling. - Alexander Nasuta; Marco Kemmerling; Daniel Lütticke; Robert H. Schmitt (LOD (1), 2023)

Evolving the Digital Industrial Infrastructure for Production: Steps Taken and the Road Ahead. - 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; et al. (CoRR, 2023)

A Data-Driven Two-Phase Multi-Split Causal Ensemble Model for Time Series. - Zhipeng Ma; Marco Kemmerling; Daniel Buschmann; Chrismarie Enslin; Daniel Lütticke; Robert H. Schmitt (Symmetry, 2023)

Beyond games: a systematic review of neural Monte Carlo tree search applications. - Marco Kemmerling; Daniel Lütticke; Robert H. Schmitt (Appl. Intell., 2024)