Maximilian Zorn, M.Sc.

Forschungsinteressen

• (Quantum/Hybrides) Reinforcement Learning
• Quantum Circuit-Construction
• Self-Replication (Eigenschaften) in Neuralen Netzwerken
• Kooperation in Multi-Agenten Systemen
• Robotik-fokussiertes Reinforcement Learning

Lehrveranstaltungen

Ausgewählte Publikationen

Alle anzeigen

• Zorn, M., Stein, J., Mansky, M., Altmann, P., Kölle. M., Linnhoff-Popien, C. & Gabor, T.
  Quality Diversity for Variational Quantum Circuit Optimization. [pdf]
  In Proceedings of the 35th International Conference on Automated Planning and Scheduling (ICAPS 2025).
  

• Zorn, M., Stein, J., Altmann, P., Kölle. M., Linnhoff-Popien, C. & Gabor, T.
  Cohesive Quantum Circuit Layer Construction with Reinforcement Learning. [pdf]
  In Proceedings of the IEEE International Conference on Quantum Computing and Engineering (QCE 2024).

• Zorn, M., Altmann, P., Stenzel, G., Kölle. M., Linnhoff-Popien, C. & Gabor, T.
  Self-Adaptive Robustness of Applied Neural-Network-Soups. [pdf]
  In Proceedings of the 2024 Conference on Artificial Life (ALIFE 2024).

• Phan, T., Ritz, F., Altmann, P., Zorn, M., Nüßlein, J., Kölle, M., Gabor, T. & Linnhoff-Popien, C.
  Attention-Based Recurrence for Multi-Agent Reinforcement Learning under Stochastic Partial Observability. [pdf]
  In Proceedings of the 40th International Conference on Machine Learning (ICML 2023).

• Zorn, M., Illium, S., Phan, T., Kaiser, T. K., Linnhoff-Popien, C. & Gabor, T.
  Social Neural Network Soups with Surprise Minimization. [pdf]
  In Proceedings of the 2023 Conference on Artificial Life (ALIFE 2023).

• Gabor, T., Zorn, M., & Linnhoff-Popien, C.
  The applicability of reinforcement learning for the automatic generation of state preparation circuits. [pdf]
  In Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO 2022).

• Gabor, T., Illium, S., Zorn, M., Lenta, C., Mattausch, A., Belzner, L., & Linnhoff-Popien, C.
  Self-replication in neural networks. [pdf]
  In Artificial Life Journal, 28(2), 2022.

• Gabor, T., Illium, S., Zorn, M., & Linnhoff-Popien, C.
  Goals for Self-Replicating Neural Networks. [pdf]
  In Proceedings of the 2021 Conference on Artificial Life (ALIFE 2021).

Community

• Peer Reviewer of (x) Publications at ECAI23 (1), NeurIPS23 (3), QCE23 (1), AAAI24 (3), ICLR24 (1), IJCAI24 (6), GECCO24 (1), RLC24 (3), QCE24 (6), QML@QCE24 (3), NeurIPS24 (6), QAIO@ICAART25 (3), ICLR24 (3), IJCAI25 (6), ICML25 (2), ALIFE25 (2), QCE25 (6), NeurIPS25 (3), QML@QCE25 (4), ICAART25 (6)
• Programm Committee at QML-Workshop QML@QCE24, QML@QCE245
• Programm Committee at QAIO-Workshop QAIO@ICAART25, QAIO@ICAART26
• Action Reviewer for Springer Nature Journal

Abschlussarbeiten

Bei Interesse einer Abschlussarbeit bitte zuerst hier informieren.

• David Engel, Maximilian Zorn, Philipp Altmann, Claudia Linnhoff-Popien, Verbesserung von kooperativem MARL durch Curriculum Learning für dynamische Rollenzuweisung, Bachelor's Thesis 2025
• Tobias Daake, Leo Sünkel, Maximilian Zorn, Claudia Linnhoff-Popien, Evolutionary Optimization of Variational Quantum Circuits for High Accuracy with Minimal Parameterized Gates, Bachelor’s Thesis 2025
• Wei Yu, Gerhard Stenzel, Maximilian Zorn, Claudia Linnhoff-Popien, Fine Tuning LLMs in Teacher Student Settings Improving Code Performance using RL, Bachelor’s Thesis 2025
• Christoph Pölt, Thomas Gabor, Maximilian Zorn, Claudia Linnhoff-Popien, Gradient Descent Optimizability of Final Productive Fitness Landscapes in Evolutionary Algorithms, Bachelor’s Thesis 2025
• Nicole Kilian, Maximilian Zorn, Philipp Altmann, Claudia Linnhoff-Popien, Efficient Reinforcement-Learning Curriculum Generation via Quality-Diversity Methods, Bachelor’s Thesis 2025
• Marcel Davignon, Maximilian Zorn, Philipp Altmann, Claudia Linnhoff-Popien, Confidence Based Robotic Grasping With Reinforcement Learning, Bachelor’s Thesis 2025
• Tim-Luis Hartenfels, Maximilian Zorn, Michael Kölle, Claudia Linnhoff-Popien, Exploring Second-Order Predator-Prey Marine Ecosystem Balance with MARL, Bachelor’s Thesis 2025
• Maria Trainer, Leo Sünkel, Maximilian Zorn, Claudia Linnhoff-Popien, Verwendung evolutionärer Algorithmen zur Optimierung von Quantum Circuits unter Berücksichtigung von Noise, Bachelor’s Thesis 2025
• Josef Stolz, Maximilian Zorn, Philipp Altmann, Claudia Linnhoff-Popien, Cooperative Sequential Robotic Manipulation with Multi-Agent Reinforcement Learning, Bachelor’s Thesis 2025
• Clarissa Kümhof, Philipp Altmann, Maximilian Zorn, Claudia Linnhoff-Popien, ​Multi-Objective Reinforcement Learning using Evolutionary Algorithms for Diverse Policy Selection, Master’s Thesis 2025
• Simon Schlichting, Leo Sünkel, Maximilian Zorn, Claudia Linnhoff-Popien, Circuit Partitioning and Genetic Optimization for Efficient Qubit Distribution in Distributed Quantum Computing, Bachelor’s Thesis 2024
• Reinhard Bittner, Thomas Gabor, Maximilian Zorn, Claudia Linnhoff-Popien, Emergent Behaviour in Self-Evaluating Genetic Programming Based on λ-Expressions, Bachelor’s Thesis, 2024
• Tom Bintener, Micheal Kölle, Maximilian Zorn, Claudia Linnhoff-Popien, Evaluating Mutation Techniques in Genetic Algorithm-Based Quantum Circuit Synthesis, Bachelor’s Thesis 2024
• Sara Oropeza, Thomas Gabor, Maximilian Zorn, Claudia Linnhoff-Popien, Update Behavior of Neural Networks Trained in Alternation with an Additional Auxiliary Task, Bachelor’s Thesis 2024
• Marie Brockschmidt, Thomas Gabor, Maximilian Zorn, Claudia Linnhoff-Popien, Evolutionary Algorithm with Similarity-Based Variation for Job-Shop, Bachelor’s Thesis 2024
• Gregor Reischl, Maximilian Zorn, Michael Kölle, Claudia Linnhoff-Popien, Learning Independent Multi-Agent Flocking Behavior With Reinforcement Learning, Bachelor’s Thesis 2024
• Julian Thomas Reff, Thomas Gabor, Maximilian Zorn, Claudia Linnhoff-Popien, Neural Networks with a Regulatory Second Task on Neuron Level, Master’s Thesis 2024
• Jonathan Philip Wulf, Jonas Stein, Maximilian Zorn, Claudia Linnhoff-Popien, State Preparation on Quantum Hardware Using an Island Genetic Algorithm, Master’s Thesis 2024
• Jonas Blenninger, Jonas Stein, Maximilian Zorn, Claudia Linnhoff-Popien, CUAOA: A Novel CUDA-Accelerated Simulation Framework for the Quantum Approximate Optimization Algorithm, Master’s Thesis 2024
• Paulin Anwander, Thomas Gabor, Maximilian Zorn, Claudia Linnhoff-Popien, Measuring Relatedness in Evolutionary Algorithms via Superfluous Genes, Bachelor’s Thesis, 2024
• Jonas Wild, Maximilian Zorn, Philipp Altmann, Claudia Linnhoff-Popien, Designing Meta-Rewards for Multi-Agent Reinforcement Learning Cooperation, Master’s Thesis 2024
• Daniel Seidl, Michael Kölle, Maximilian Zorn, Claudia Linnhoff-Popien, Evaluierung von metaheuristischen Optimierungsalgorithmen für Quantum Reinforcement Learning, Master’s Thesis 2024
• Ioan-Luca Ionescu, Maximilian Zorn, Fabian Ritz, Claudia Linnhoff-Popien, Specification Aware Evolutionary Error Search in Parameterized RL Environments, Master’s Thesis, 2024
• Clara Goldmann, Fabian Ritz, Maximilian Zorn, Claudia Linnhoff-Popien, Balancing Populations with Multi-Agent Reinforcement Learning, Master’s Thesis, 2024
• Simon Hackner, Philipp Altmann, Maximilian Zorn, Claudia Linnhoff-Popien, Diversity-Driven Pre-Training for Efficient Transfer RL, Bachelor’s Thesis, 2023
• Moritz Glawleschkoff, Thomas Gabor, Maximilian Zorn, Claudia Linnhoff-Popien. Empowerment for Evolutionary Algorithms. Bachelor’s Thesis, 2023
• Matthias Fruth, Fabian Ritz, Maximilian Zorn, Claudia Linnhoff-Popien. The Impact of Action Order in Multi-Agent Reinforcement Learning. Master’s Thesis, 2023