An offline approach to fNIRS-guided reinforcement learning for robot behavior

Source: arXiv cs.RO·2026-08-25 12:00Publish time unverified

arXiv:2607.14393v2 Announce Type: replace Abstract: Human-in-the-loop Reinforcement Learning has become a popular approach for training, finetuning, and aligning robot behavior with user preferences. Our paper explores the feasibility of using brain signals via functional near-infrared spectroscopy (fNIRS) to modulate robot learning in simulation.