4 citations · 17 across the 10 of their papers we have counts for
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cs.AI2025
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.…
cs.AI2020★ 4 cited
SPOTTER: Extending Symbolic Planning Operators through Targeted Reinforcement Learning
Vasanth Sarathy, Daniel Kasenberg, Shivam Goel +2
Symbolic planning models allow decision-making agents to sequence actions in arbitrary ways to achieve a variety of goals in dynamic domains. However, they are typically handcrafte…