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Philipp Altmann, M.Sc. Lehrstuhl für Mobile und Verteilte Systeme Ludwig-Maximilians-Universität München, Oettingenstraße 67 Raum E105 Telefon: +49 89 / 2180-9421 Fax: +49 89 / 2180-9148 |
Research Interests
- Collective Intelligence
- Reinforcement Learning
- Quantum Machine Learning
- Surrogate Modeling
- Explainability
Publications
- Philipp Altmann, Adelina Bärligea, Jonas Stein, Michael Kölle, Thomas Gabor, Thomy Phan, and Claudia Linnhoff-Popien, „Quantum Circuit Design: A Reinforcement Learning Challenge“, in Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2024), 2024, to appear. [preprint]
- Proceedings of the 16th International Conference on Agents and Artificial Intelligence: ICAART, 2024.
- Leo Sünkel, Philipp Altmann, Michael Kölle, and Thomas Gabor, „Quantum Federated Learning for Image Classification“, in Proceedings of the 16th International Conference on Agents and Artificial Intelligence: ICAART, 2024.
- Michael Kölle, Mohamad Hgog, Fabian Ritz, Philipp Altmann, Maximilian Zorn, Jonas Stein, and Claudia Linnhoff-Popien, „Quantum Advantage Actor-Critic for Reinforcement Learning“, in Proceedings of the 16th International Conference on Agents and Artificial Intelligence: ICAART, 2024.
- Jonas Stein, Michael Poppel, Philip Adamczyk, Ramona Fabry, Zixin Wu, Michael Kölle, Jonas Nüßlein, Daniëlle Schuman, Philipp Altmann, Thomas Ehmer, Vijay Narasimha, and Claudia Linnhoff-Popien, „Benchmarking Quantum Surrogate Models on Scarce and Noisy Data“, in Proceedings of the 16th International Conference on Agents and Artificial Intelligence: ICAART, 2024.
- Michael Kölle, Tom Schubert, Philipp Altmann, Maximilian Zorn, Jonas Stein, and Claudia Linnhoff-Popien, „A Reinforcement Learning Environment for Directed Quantum Circuit Synthesis“, in Proceedings of the 16th International Conference on Agents and Artificial Intelligence: ICAART, 2024.
- Jonas Stein, Navid Roshani, Maximilian Zorn, Philipp Altmann, Michael Kölle, and Claudia Linnhoff-Popien, „Improving Parameter Training for VQEs by Sequential Hamiltonian Assembly“, in Proceedings of the 16th International Conference on Agents and Artificial Intelligence: ICAART, 2024.
- Michael Kölle, Felix Topp, Thomy Phan, Philipp Altmann, Jonas Nüßlein, and Claudia Linnhoff-Popien, „Multi-Agent Quantum Reinforcement Learning Using Evolutionary Optimization“, in Proceedings of the 16th International Conference on Agents and Artificial Intelligence: ICAART
- Tomography Scans“ in IEEE International Conference on Quantum Computing and Engineering (QCE)
- IEEE International Conference on Quantum Computing and Engineering (QCE)
- Philipp Altmann, Fabian Ritz, Leonard Feuchtinger, Jonas Nüßlein, Claudia Linnhof-Popien, and Thomy Phan „CROP: Towards Distributional-Shift Robust Reinforcement Learning using Compact Reshaped Observation Processing“, in 32nd International Joint Conference on Artificial Intelligence (IJCAI ’23), 2023, pp. 3414-3422. [DOI][preprint][source]
- Thomy Phan, Fabian Ritz, Philipp Altmann, Maximilian Zorn, Jonas Nüßlein, Michael Kölle, Thomas Gabor, and Claudia Linnhoff-Popien, „Attention-Based Recurrence for Multi-Agent Reinforcement Learning under Stochastic Partial Observability“, in 40th International Conference on Machine Learning (ICML ’23), 2023. [PDF][preprint][source]
- Philipp Altmann, Thomy Phan, Fabian Ritz, Claudia Linnhoff-Popien, and Thomas Gabor „DIRECT: Learning from Sparse and Shifting Rewards using Discriminative Reward Co-Training“, in 15th Adaptive and Learning Agents Workshop (ALA), 2023. [PDF][preprint]
- Philipp Altmann, Leo Sünkel, Jonas Stein, Tobias Müller, Christoph Roch and Claudia Linnhoff-Popien, “SEQUENT: Towards Traceable Quantum Machine Learning using Sequential Quantum Enhanced Training“, in Proceedings of the 15th International Conference on Agents and Artificial Intelligence – Volume 3: ICAART, 2023, pp.744-751. [DOI][PDF][preprint]
- Michael Kölle, Tim Matheis, Philipp Altmann, and Kyrill Schmid, „Learning to Participate Through Trading of Reward Shares“, in Proceedings of the 15th International Conference on Agents and Artificial Intelligence – Volume 1: ICAART, 2023, pp. 355-362. [DOI][PDF][preprint]
- Fabian Ritz, Thomy Phan, Andreas Sedlmeier, Philipp Altmann, Jan Wieghardt, Reiner Schmid, Horst Sauer, Cornel Klein, Claudia Linnhoff-Popien and Thomas Gabor, „Capturing Dependencies within Machine Learning via a Formal Process Model“, in Leveraging Applications of Formal Methods, Verification and Validation. Adaptation and Learning. ISOLA 2022, Lecture Notes in Computer Science, vol 13703, Springer International Publishing, pp.249–265. [DOI][preprint]
- Thomy Phan, Felix Sommer, Philipp Altmann, Fabian Ritz, Lenz Belzner, and Claudia Linnhoff-Popien, „Emergent Cooperation from Mutual Acknowledgment Exchange“, in 21st Conference on Autonomous Agents and Multiagent Systems (AAMAS ’22), 2022, pp. 1047–1055. [PDF][source]
- Tobias Müller, Christoph Roch, Kyrill Schmid and Philipp Altmann, „Towards Multi-agent Reinforcement Learning using Quantum Boltzmann Machines“, in Proceedings of the 14th International Conference on Agents and Artificial Intelligence – Volume 1: ICAART, 2022, pp. 121-130. [DOI][PDF][preprint]
- Thomy Phan, Fabian Ritz, Lenz Belzner, Philipp Altmann, Thomas Gabor, and Claudia Linnhoff-Popien, „VAST: Value Function Factorization with Variable Agent Sub-Teams“, in 35th Conference on Neural Information Processing Systems (NeurIPS ’21), 2021. [PDF][source]
- Thomas Gabor and Philipp Altmann. Benchmarking surrogate-assisted genetic recommender systems. In Proceedings of the Genetic and Evolutionary Computation Conference Companion, pages 1568-1575, 2019. [DOI][preprint]
Teaching
- Affective Computing – Empathic Artificial Intelligence:
SoSe24, WS23/24, SoSe23, WS22/23, SoSe22, WS21/22, SoSe21 - Autonomous Systems (Practical Course):
SoSe24, WS23/24, SoSe23, WS22/23 - Working Group Artificial Intelligence:
SoSe24, WS23/24, SoSe23
Theses
- Simon Hackner, Philipp Altmann, Maximilian Zorn, Claudia Linnhoff-Popien, „Diversity-Driven Pre-Training for Efficient Transfer Reinforcement Learning”, 2023.
- Katharina Winter, Philipp Altmann, Thomy Phan, Claudia Linnhoff-Popien, „Consensus-Based Mutual Acknowledgment Token Exchange”, 2023.
- Tom Schubert, Michael Kölle, Philipp Altmann, Claudia Linnhoff-Popien, „A Reinforcement Learning Environment for directed Quantum Circuit Synthesis”, 2023.
- Sarah Gerner, Thomas Gabor, Philipp Altmann, Claudia Linnhoff-Popien, „Final Productive Fitness in Evolutionary Algorithms and its Approximation via Neural Network Surrogates”, 2023.
- Jonas Maurer, Michael Kölle, Philipp Altmann, Claudia Linnhoff-Popien, „Dimensionality Reduction with Autoencoders for Efficient Classification with Variational Quantum Circuits”, 2023.
- Alain Feimer, Thomy Phan, Philipp Altmann, Claudia Linnhoff-Popien, „Generalization in Multi-Agent Reinforcement Learning using Minimax Learning“, 2023.
- Arnold Unterauer, Thomy Phan, Philipp Altmann, Claudia Linnhoff-Popien, „Hidden Attacks in Multi-Agent Reinforcement Learning“, 2023.
- Leonard Feuchtinger, Philipp Altmann, Fabian Ritz, Claudia Linnhoff-Popien, „Distributional Shift in Reinforcement Learning – Learning from a single gridworld“, 2022.
- Marco Börner, Thomy Phan, Philipp Altmann, Claudia Linnhoff-Popien „Predicting the optimal approximation level for Quantum Annealing“, 2022.
- Felix Sommer, Thomy Phan, Philipp Altmann, Claudia Linnhoff-Popien „Learning Trust in Multi-Agent Systems“, 2020.
Community
- 11th International Conference on Affective Computing and Intelligent Interaction (ACII 2023): Program Committee
- 37th Conference on Neural Information Processing Systems (NeurIPS 2023): Reviewer
- 12th International Conference on Learning Representations (ICLR 2024): Reviewer
- Neural Computing and Applications: Reviewer
- 41st International Conference on Machine Learning (ICML 2024): Reviewer
- 33rd International Joint Conference on Artificial Intelligence (IJCAI 2024): Program Committee
- 1st Reinforcement Learning Conference (RLC 2024): Reviewer
