Documents of the Department

• Master Theses
• Bachelor Theses

• Bahrami, Sepideh: Enhancing HTN planning with deep reinforcement learning for method selection, Master Thesis No. 51, 2025.
• Bhat, Varun Rajesh: Enhancing HTN planning with large language models and case-based retrieval for automated domain generation, Master Thesis No. 47, 2025.
• Gaikwad, Paul: Evaluating Messaging Middleware for Distributed Communication and Testing: An Automotive Perspective, Master Thesis No. 26, 2025.
• Hösch, Peter: Towards a Neuro-Symbolic Approach for Occupant Activity Recognition: Combining Temporal HTN Planning with Hidden Markov Models, Master Thesis No. 1, 2025.
• Huang, Ho: Investigation of Time Synchronization Primitives in Global Distributed Testing of Automotive ECUs, Master Thesis No. 32, 2025.
• Kashyap, Ananth Mahesh: Evaluating Cloud-Native Approaches for a Knowledge Synchronization System: A Comparative Study Focused on Serverless Containerization, Master Thesis No. 40, 2025.
• Kunz, Philipp: Towards a framework for algorithm learning: cross-domain induction and the principled limits of algorithmic abstraction, Master Thesis No. 54, 2025.
• Nabakowski, Lukas: Replanning in risk aware HTN planning, Master Thesis No. 41, 2025.
• Nguyen, Duc Anh: Quantum circuit optimization for circuit cutting, Master Thesis No. 29, 2025.
• Panchal, Utsav: Multi-human behavior prediction using vision language models, Master Thesis No. 14, 2025.
• Sharma, Barkha: Classification, Comparison, and Analysis of AI Planning Tools: A Systematic Multivocal Literature Review, Master Thesis No. 2, 2025.
• Shetye, Srushti: An LLM-modulo framework for automated PDDL domain model generation, Master Thesis No. 56, 2025.
• Stiliadou, Sharon-Naemi: Design of a quantum low-code framework, Master Thesis No. 31, 2025.
• Tarpan, Sena: Leveraging LLMs for Database Interaction with Structured and Unstructured Data in the Context of Automotive Engineering, Master Thesis No. 13, 2025.
• Weber, Jan: Assisted data migrations for MUSE4Anything, Master Thesis No. 9, 2025.

• Elis, Daniel: Investigating the potential of large language models to enhance AI planner efficiency through automated domain model configuration, Bachelor Thesis No. 47, 2025.
• Kästner, Johannes: Analyzing realistic aspects of AI planning knowledge models, Bachelor Thesis No. 46, 2025.
• Larionov, Andrey: Development of data visualization plugins for QHAna, Bachelor Thesis No. 3, 2025.
• Layer, Leon: Enhancing quantum state analysis with QHAna plugins for quantum neural networks research, Bachelor Thesis No. 21, 2025.
• Mürwald, Alina: Integrating curvature into the cost landscape of variational quantum algorithms, Bachelor Thesis No. 36, 2025.
• Rezk, Ahmed: Annotations for Quantum Circuit Optimization and Provenance Management, Bachelor Thesis No. 7, 2025.
• Schmid, Anton: Uncertainty aspects in Texas hold'em poker AIs: a comparative analysis, Bachelor Thesis No. 48, 2025.
• Six, Daniel: Towards advancing modular AI planning systems : insights from the PlanX toolbox redesign, Bachelor Thesis No. 17, 2025.
• Tekin, Serhat: The impact of domain models on energy consumption of classical planners, Bachelor Thesis No. 61, 2025.
• Vintonyak, Roman: Automating deployment and testing in distributed networks of Electronic Control Units, Bachelor Thesis No. 6, 2025.
• Walcher, Lukas: Personalization of routing for drivers through recognition and analysis of individual preferences, Bachelor Thesis No. 2, 2025.