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Preference-Conditioned Multi-Objective Reinforcement Learning for Tactical Decision Making in Heavy-Duty Vehicles

Single source1 source12 Oct 2026

arXiv:2601.18783v3 Announce Type: replace-cross Abstract: A central difficulty in applying reinforcement learning to real-world applications such as autonomous driving is that conventional scalar reward formulations obtained by aggregating multiple often compe

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arxiv.orghttps://arxiv.org/abs/2601.18783

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