Robust Parameter Estimation and Tracking through Lyapunov-based Actor-Critic Reinforcement Learning. - Thomas Rudolf; Joshua Ransiek; Stefan Schwab; Sören Hohmann (IECON, 2022)

Generation of Adversarial Trajectories using Reinforcement Learning to Test Motion Planning Algorithms. - Joshua Ransiek; Barbara Schütt; Adrian Hof; Eric Sax (ITSC, 2023)

1001 Ways of Scenario Generation for Testing of Self-driving Cars: A Survey. - Barbara Schütt; Joshua Ransiek; Thilo Braun; Eric Sax (IV, 2023)

Contextualizing the Sim-to-Real Gap for Hardware-in-the-Loop Testing of Highly Automated Driving Functions. - Christian Steinhauser; Joshua Ransiek; Jacob Langner; Eric Sax (ICSRS, 2024)

GOOSE: Goal-Conditioned Reinforcement Learning for Safety-Critical Scenario Generation. - Joshua Ransiek; Johannes Plaum; Jacob Langner; Eric Sax (ITSC, 2024)

Disentangling Uncertainty for Safe Social Navigation using Deep Reinforcement Learning. - Daniel Flögel; Marcos Gómez Villafañe; Joshua Ransiek; Sören Hohmann (CoRR, 2024)

Adversarial and Reactive Traffic Agents for Realistic Driving Simulation. - Joshua Ransiek; Philipp Reis; Eric Sax (CoRR, 2024)

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording. - Philipp Reis; Joshua Ransiek; David Petri; Jacob Langner; Eric Sax (CoRR, 2025)