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Publications, Faculty of Engineering, HTWK Leipzig

Research Profile: Robotics, Control & AI

Mechanisms and Principles of Evolutionary Algorithms and Reinforcement Learning

  • Julian Ziegler, Patrick Frenzel, Mirco Fuchs: Utilising Reinforcement Learning for Bottom-Up Part-Wise Reconstruction of 2D Wire-Frame Projections, Accepted at the 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 optimisation using stochastic Lyapunov functions and quantifier elimination. SN Computer Science, 2, 1–12.
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