XCS for Self-awareness in Autonomous Computing Systems
T. Hansmeier, XCS for Self-Awareness in Autonomous Computing Systems, 2023.

Compute Centers I: Heterogeneous Execution Environments
T. Hansmeier, T. Kenter, M. Meyer, H. Riebler, M. Platzner, C. Plessl, 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, Heinz Nixdorf Institut, Universität Paderborn, Paderborn, 2023, pp. 165–182.

An Evaluation of XCS on the OpenAI Gym
F. Mehlich, An Evaluation of XCS on the OpenAI Gym, Paderborn University, Paderborn, 2023.

On-The-Fly Computing -- Individualized IT-services in dynamic markets
C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, H. Wehrheim, On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets, Heinz Nixdorf Institut, Universität Paderborn, Paderborn, 2023.

Multi-FPGA Designs and Scaling of HPC Challenge Benchmarks via MPI and Circuit-Switched Inter-FPGA Networks
M. Meyer, T. Kenter, C. Plessl, ACM Transactions on Reconfigurable Technology and Systems (2023).

Integrating Safety Guarantees into the Learning Classifier System XCS
T. Hansmeier, M. Platzner, in: Applications of Evolutionary Computation, EvoApplications 2022, Proceedings, Springer International Publishing, 2022, pp. 386–401.

XCS on Embedded Systems: An Analysis of Execution Profiles and Accelerated Classifier Deletion
T. Hansmeier, M. Brede, M. Platzner, in: GECCO ’22: Proceedings of the Genetic and Evolutionary Computation Conference Companion, Association for Computing Machinery (ACM), New York, NY, United States, 2022, pp. 2071–2079.

Hardware Trojans in Reconfigurable Computing
Q.A. Ahmed, Hardware Trojans in Reconfigurable Computing,  Paderborn University, Paderborn, Germany, Paderborn, 2022.

A Comparison of Machine Learning Techniques for the On-line Characterization of Tasks Executed on Heterogeneous Compute Nodes
C. Kashikar, A Comparison of Machine Learning Techniques for the On-Line Characterization of Tasks Executed on Heterogeneous Compute Nodes, Paderborn University, Paderborn, 2021.

Implementation and Profiling of XCS in the Context of Embedded Systems
M. Brede, Implementation and Profiling of XCS in the Context of Embedded Systems, Paderborn University, Paderborn, 2021.

Self-aware Operation of Heterogeneous Compute Nodes using the Learning Classifier System XCS
T. Hansmeier, in: HEART ’21: Proceedings of the 11th International Symposium on Highly Efficient Accelerators and Reconfigurable Technologies, Association for Computing Machinery (ACM), New York, NY, United States, 2021.

An Experimental Comparison of Explore/Exploit Strategies for the Learning Classifier System XCS
T. Hansmeier, M. Platzner, in: GECCO ’21: Proceedings of the Genetic and Evolutionary Computation Conference Companion, Association for Computing Machinery (ACM), New York, NY, United States, 2021, pp. 1639–1647.

An Adaption Mechanism for the Error Threshold of XCSF
T. Hansmeier, P. Kaufmann, M. Platzner, in: GECCO ’20: Proceedings of the Genetic and Evolutionary Computation Conference Companion, Association for Computing Machinery (ACM), New York, NY, United States, 2020, pp. 1756–1764.

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

A Case for a New IT Ecosystem: On-The-Fly Computing
H. Karl, D. Kundisch, F. Meyer auf der Heide, H. Wehrheim, Business &; Information Systems Engineering 62 (2020) 467–481.

Transparent Acceleration for Heterogeneous Platforms with Compilation to OpenCL
H. Riebler, G.F. Vaz, T. Kenter, C. Plessl, ACM Trans. Archit. Code Optim. (TACO) 16 (2019) 14:1–14:26.

Using Just-in-Time Code Generation to Transparently Accelerate Applications in Heterogeneous Systems
G.F. Vaz, Using Just-in-Time Code Generation to Transparently Accelerate Applications in Heterogeneous Systems, Universität Paderborn, 2019.

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

Efficient parallel branch-and-bound search on FPGAs using work stealing and instance-specific designs
H. Riebler, Efficient Parallel Branch-and-Bound Search on FPGAs Using Work Stealing and Instance-Specific Designs, 2019.

Ampehre: An Open Source Measurement Framework for Heterogeneous Compute Nodes
A. Lösch, A. Wiens, M. Platzner, in: Proceedings of the International Conference on Architecture of Computing Systems (ARCS), Springer International Publishing, Cham, 2018, pp. 73–84.