Multi-Grid Methods for Reinforcement Learning in Controlled Diffusion Processes. - Stephan Pareigis (NIPS, 1996)

Lernen der Lösung der Bellman-Gleichung durch Beobachtung von kontinuierlichen Prozessen. - Stephan Pareigis (1996)

Adaptive Choice of Grid and Time in Reinforcement Learning. - Stephan Pareigis (NIPS, 1997)

FAUST: Entwicklung von Fahrerassistenz- und autonomen Systemen - Technische Informatik an der Hochschule für Angewandte Wissenschaften Hamburg. - Stephan Pareigis; Bernd Schwarz; Franz Korf (PEARL, 2007)

Miniature Autonomy as One Important Testing Means in the Development of Machine Learning Methods for Autonomous Driving: How ML-based Autonomous Driving could be Realized on a 1: 87 Scale. - Tim Tiedemann; Jonas Fuhrmann; Sebastian Paulsen; Thorben Schnirpel; Nils Schönherr; Bettina Buth; Stephan Pareigis (ICINCO (2), 2019)

Miniaturautonomie und Echtzeitsysteme. - Stephan Pareigis; Tim Tiedemann; Jonas Fuhrmann; Sebastian Paulsen; Thorben Schnirpel; Nils Schönherr (Echtzeit, 2019)

Künstliche Intelligenz in der Miniaturautonomie. - Stephan Pareigis; Tim Tiedemann; Markus Kasten; Morten Stehr; Thorben Schnirpel; Luk Schwalb; Henri Burau (Echtzeit, 2020)

Robust Neural Network for Sim-to-Real Gap in End-to-End Autonomous Driving. - Stephan Pareigis; Fynn Luca Maaß (ICINCO, 2022)

Miniature Autonomy as Means to Find New Approaches in Reliable Autonomous Driving AI Method Design. - Tim Tiedemann; Luk Schwalb; Markus Kasten; Robin Grotkasten; Stephan Pareigis (Frontiers Neurorobotics, 2022)

Offline Feature-Based Reinforcement Learning with Preprocessed Image Inputs for Liquid Pouring Control. - Stephan Pareigis; Jesus Eduardo Hermosilla-Diaz; Jeeangh Jennessi Reyes-Montiel; Fynn Luca Maaß; Helen Haase; Maximilian Mang; Antonio Marín-Hernández (ICINCO (1), 2023)

Miniature Autonomous Vehicle Environment for Sim-to-Real Transfer in Reinforcement Learning. - Stephan Pareigis; Daniel Riege; Tim Tiedemann (ICINCO (1), 2024)