Knowledge Self-Adaptive Multi-Agent Learning. - Simon Reichhuber (GI-Jahrestagung (Workshops), 2019)

Opportunistic Meta-Learning: A Case Study for Quality Assurance in Industry 4.0 Environments. - Simon Reichhuber; Sven Tomforde (ACSOS Companion, 2020)

Opportunistic Knowledge Adaption in Self-Learning Systems. - Simon Reichhuber; Sven Tomforde (ACSOS Companion, 2020)

Improvements to Increase the Efficiency of the AlphaZero Algorithm: A Case Study in the Game 'Connect 4'. - Colin Clausen; Simon Reichhuber; Ingo Thomsen; Sven Tomforde (ICAART (2), 2021)

Bet-based Evolutionary Algorithms: Self-improving Dynamics in Offspring Generation. - Simon Reichhuber; Sven Tomforde (ICAART (2), 2021)

Evolving Gaussian Mixture Models for Classification. - Simon Reichhuber; Sven Tomforde (ICAART (3), 2022)

Active Reinforcement Learning - A Roadmap Towards Curious Classifier Systems for Self-Adaptation. - Simon Reichhuber; Sven Tomforde (CoRR, 2022)

Exotic Bets: Evolutionary Computing Coupled with Bet Mechanisms for Model Selection. - Simon Reichhuber; Sven Tomforde (ICAART (2), 2023)

From Simulated to Real Environments: Q-Learning for MAZE-Navigation of a TurtleBot. - Tobias Weiss; Simon Reichhuber; Sven Tomforde (ICAISC (2), 2023)

Learning Occlusions in Robotic Systems: How to Prevent Robots from Hiding Themselves. - Jakob Nazarenus; Simon Reichhuber; Manuel Amersdorfer; Lukas Elsner; Reinhard Koch; Sven Tomforde; Hossam Abbas (ICAART (2), 2024)

Occlusion Avoidance for Robotic Manipulators Using Rigid Gaussian Splatting. - Jakob Nazarenus; Simon Reichhuber; Reinhard Koch; Sven Tomforde; Simin Kou; Fang-Lue Zhang (SN Comput. Sci., 2025)