From the 1 of 3 linked papers with an AI index.
3 papers
An offline approach to fNIRS-guided reinforcement learning for robot behavior
Julia Santaniello, Madelaine Brower, Benson Jiang +4
The paper investigates using offline functional near‑infrared spectroscopy (fNIRS) brain signals to augment reinforcement learning for robot behavior, showing that neural data can…
Towards Reinforcement Learning from Neural Feedback: Mapping fNIRS Signals to Agent Performance
Julia Santaniello, Matthew Russell, Benson Jiang +3
Reinforcement Learning from Human Feedback (RLHF) is a methodology that aligns agent behavior with human preferences by integrating user feedback into the agent's training process.…
Mapping Neural Signals to Agent Performance, A Step Towards Reinforcement Learning from Neural Feedback
Julia Santaniello, Matthew Russell, Benson Jiang +3
Implicit Human-in-the-Loop Reinforcement Learning (HITL-RL) is a methodology that integrates passive human feedback into autonomous agent training while minimizing human workload.…