Publikationen Fakultät Ingenieurwissenschaften HTWK Leipzig
Forschungsprofil Robotics, Control & AI
Mechanisms and Principles of Evolutionary Algorithms and Reinforcement Learning
- Julian Ziegler, Patrick Frenzel, Mirco Fuchs: Utilizing Reinforcement Learning for Bottom-Up part-wise Reconstruction of 2D Wire-Frame Projections, Accepted at 2025 Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM), arxiv.org/pdf/2503.16629
- Richter, H., & Thomson, S. L. (2024). Information flow and Laplacian dynamics on local optima networks. In 2024 IEEE Congress on Evolutionary Computation (CEC) (pp. 1-8). IEEE.
- Richter, H. (2023). Spectral dynamics of guided edge removals and identifying transient amplifiers for death–Birth updating. Journal of Mathematical Biology, 87(1), 3
- Richter, H. (2021). Spectral analysis of transient amplifiers for death–birth updating constructed from regular graphs. Journal of Mathematical Biology, 82(7), 61
- Richter, H. (2019). Properties of network structures, structure coefficients, and benefit-to-cost ratios. Biosystems, 180, 88-100.
- Richter, H., & Nörenberg, P. M. (2024). Random and Chaotic Sequences, and the Effect of their Distributions on PSO Performance. In 2024 IEEE Congress on Evolutionary Computation (CEC) (pp. 1-8). IEEE.
- Nörenberg, P. M., & Richter, H. (2023). Do Random and Chaotic Sequences Really Cause Different PSO Performance? GECCO '23 Companion: Proceedings of the Companion Conference on Genetic and Evolutionary Computation, 99-102
- Gerwien, M., Voßwinkel, R., & Richter, H. (2021). Algebraic stability analysis of particle swarm optimization using stochastic Lyapunov functions and quantifier elimination. SN Computer Science, 2, 1-12.