pbrl

MoonOut4 个月前
pbrl
RIME：用交叉熵 loss 大小分辨 preference 是否正确 + 内在奖励预训练 reward modelPreference-based Reinforcement Learning (PbRL) circumvents the need for reward engineering by harnessing human preferences as the reward signal. However, current PbRL methods excessively depend on high-quality feedback from domain experts, which results i
MoonOut8 个月前
pbrl
PbRL | Preference Transformer：反正感觉 transformer 很强大Preference-based reinforcement learning (RL) provides a framework to train agents using human preferences between two behaviors. However, preference-based RL has been challenging to scale since it requires a large amount of human feedback to learn a rewar