Alexander Lodemann, M.Sc.

PhD Project:

Planning the Unplannable: Leveraging Automated Planning to Guide Medical Procedures

Alexander Lodemann joined the Institute of Artificial Intelligence in March 2025. He received his M.Sc. in Computer Science from Ulm University in 2025, where he specialized in AI planning with a focus on hierarchical planning.
Currently, he is pursuing his PhD under the supervision of Prof. Dr. Birte Glimm, working on methods for automated knowledge acquisition both from a theoretical and practical point of view.
His broader research explores how to reduce the burden of hand-crafted planning models with the goal of enabling planning systems to operate in real-world environments that offer enough documentation but lack formalized domain models.

Research Interests

• AI Planning
• Domain Modeling Support
• Domain Learning
• Hierarchical Planning

Activities

• 2025: Program Committee (PC) member HPlan2025
• 2020: Participation in the iGEM competition (Team iGEM_UUlm) - bronze medal

Publications

Peer-Reviewed

• C. Olz, A. Lodemann, B. Jutz, M. Schmautz, M. Borowiec, S. Biundo and P. Bercher, “An Extensive Empirical Evaluation of Inferring Preconditions and Effects of Compound Tasks in Ground HTN Planning Problems”, Journal of Artificial Intelligence Research, vol. 82, pp. 1407-1444, Mä. 2025. https://jair.org/index.php/jair/article/view/17279
• M. Welt, A. Lodemann, C. Olz, P. Bercher and B. Glimm, “Calculating Optimal Corrections for Unsolvable Planning Problems” in Proceedings of the 28th European Conference on Artificial Intelligence (ECAI 2025), IOS Press, 2025
• C. Olz, A. Lodemann and P. Bercher, “A Heuristic for Optimal Total-Order HTN Planning Based on Integer Linear Programming” in Proceedings of the 27th European Conference on Artificial Intelligence (ECAI 2024), IOS Press, 2024, pp. 4303–4310
• C. Olz, A. Lodemann and P. Bercher, “An ILP Heuristic for Total-Order HTN Planning” in Proceedings of the 7th ICAPS Workshop on Hierarchical Planning (HPlan 2024), 2024