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cs.LG2024
Offline Hierarchical Reinforcement Learning via Inverse Optimization
Carolin Schmidt, Daniele Gammelli, James Harrison +2
Hierarchical policies enable strong performance in many sequential decision-making problems, such as those with high-dimensional action spaces, those requiring long-horizon plannin…
cs.LG2024★ 1 cited
A Large-Scale Analysis on the Use of Arrival Time Prediction for Automated Shuttle Services in the Real World
Carolin Schmidt, Mathias Tygesen, Filipe Rodrigues
Urban mobility is on the cusp of transformation with the emergence of shared, connected, and cooperative automated vehicles. Yet, for them to be accepted by customers, trust in the…