Hansmeier, T., Kenter, T., Meyer, M., Riebler, H., Platzner, M., &; Plessl, C. (2023). Compute Centers I: Heterogeneous Execution Environments. In C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, &; H. Wehrheim (Eds.), On-The-Fly Computing -- Individualized IT-services in dynamic markets (Vol. 412, pp. 165–182). Heinz Nixdorf Institut, Universität Paderborn.https://doi.org/10.5281/zenodo.8068642 

Hansmeier, T., &; Platzner, M. (2022). Integrating Safety Guarantees into the Learning Classifier System XCS. Applications of Evolutionary Computation, EvoApplications 2022, Proceedings, 13224, 386–401.https://doi.org/10.1007/978-3-031-02462-7_25 

Hansmeier, T., Brede, M., &; Platzner, M. (2022). XCS on Embedded Systems: An Analysis of Execution Profiles and Accelerated Classifier Deletion. GECCO ’22: Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2071–2079.https://doi.org/10.1145/3520304.3533977 

Hansmeier, T. (2021). Self-aware Operation of Heterogeneous Compute Nodes using the Learning Classifier System XCS. HEART ’21: Proceedings of the 11th International Symposium on Highly Efficient Accelerators and Reconfigurable Technologies. International Symposium on Highly Efficient Accelerators and Reconfigurable Technologies (HEART ’21), Online.https://doi.org/10.1145/3468044.3468055 

Hansmeier, T., &; Platzner, M. (2021). An Experimental Comparison of Explore/Exploit Strategies for the Learning Classifier System XCS. GECCO ’21: Proceedings of the Genetic and Evolutionary Computation Conference Companion, 1639–1647.https://doi.org/10.1145/3449726.3463159 

Hansmeier, T., Kaufmann, P., &; Platzner, M. (2020). An Adaption Mechanism for the Error Threshold of XCSF. GECCO ’20: Proceedings of the Genetic and Evolutionary Computation Conference Companion, 1756–1764.https://doi.org/10.1145/3377929.3398106 

Hansmeier, T., Kaufmann, P., &; Platzner, M. (2020). Enabling XCSF to Cope with Dynamic Environments via an Adaptive Error Threshold. In GECCO ’20: Proceedings of the Genetic and Evolutionary Computation Conference Companion (pp. 125–126). New York, NY, United States: Association for Computing Machinery (ACM).https://doi.org/10.1145/3377929.3389968 

Hansmeier, T., Platzner, M., Pantho, M. J. H., &; Andrews, D. (2019). An Accelerator for Resolution Proof Checking based on FPGA and Hybrid Memory Cube Technology. Journal of Signal Processing Systems, 91(11), 1259–1272.https://doi.org/10.1007/s11265-018-1435-y 

Hansmeier, T. (2019). Autonomous Operation of High-Performance Compute Nodes through Self-Awareness and Learning Classifiers. Universität Paderborn.

Hansmeier, T., Platzner, M., &; Andrews, D. (2018). An FPGA/HMC-Based Accelerator for Resolution Proof Checking. In ARC 2018: Applied Reconfigurable Computing. Architectures, Tools, and Applications (Vol. 10824, pp. 153–165). Santorini, Greece: Springer International Publishing.https://doi.org/10.1007/978-3-319-78890-6_13 

Hansmeier, T. (2017). An FPGA Accelerator for Checking Resolution Proofs. Universität Paderborn.