229 citations · 329 across the 32 of their papers we have counts for
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cs.LG2025
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.…
cs.LG2020★ 229 cited
Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey
Sanmit Narvekar, Bei Peng, Matteo Leonetti +3
Reinforcement learning (RL) is a popular paradigm for addressing sequential decision tasks in which the agent has only limited environmental feedback. Despite many advances over th…