3 papers
cs.LG2026
CIG: Exploration via Conditional Information Gain
Tim Joseph, Marcus Fechner, Philipp Stegmaier +2
Intrinsic rewards for exploration in reinforcement learning condition on different contexts: lifelong rewards score each transition against accumulated experience but ignore within…
cs.RO2026
Automatic Curriculum Learning for Driving Scenarios: Towards Robust and Efficient Reinforcement Learning
Ahmed Abouelazm, Tim Weinstein, Tim Joseph +2
This paper addresses the challenges of training end-to-end autonomous driving agents using Reinforcement Learning (RL). RL agents are typically trained in a fixed set of scenarios…
cs.RO2026
Balancing Progress and Safety: A Novel Risk-Aware Objective for RL in Autonomous Driving
Ahmed Abouelazm, Jonas Michel, Helen Gremmelmaier +3
Reinforcement Learning (RL) is a promising approach for achieving autonomous driving due to robust decision-making capabilities. RL learns a driving policy through trial and error…