Can i have recent papers on reinforcement learning with human feedback?
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Recent papers on reinforcement learning with human feedback have focused on addressing the challenges of limited human feedback, bounded rationality of human decisions, and off-policy distribution shift. One approach is to use the Dynamic Discrete Choice (DDC) model to model and understand human choices. Li et al. propose a Dynamic-Choice-Pessimistic-Policy-Optimization (DCPPO) method that estimates the human behavior policy and the state-action value function, recovers the human reward function, and finds a near-optimal policy . Wu and Zhang present a method that uses scores provided by humans to improve the feedback efficiency of interactive reinforcement learning, enabling the learning paradigm to be insensitive to imperfect or unreliable scores . Zhan et al. investigate offline reinforcement learning with human feedback in the form of preference between trajectory pairs and provide a novel guarantee for learning any target policy with a polynomial number of samples .
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| Papers (5) | Insight |
|---|---|
| The provided paper is about offline reinforcement learning with human feedback, but it does not mention recent papers on the topic. | |
24 May 2023 | The provided paper is about offline reinforcement learning with human feedback, but it does not mention recent papers on the topic. |
| The provided paper is about a new method that uses scores provided by humans to improve the feedback efficiency of interactive reinforcement learning. It does not mention recent papers on reinforcement learning with human feedback. | |
28 May 2023 | The provided paper is about offline Reinforcement Learning with Human Feedback (RLHF) and proposes a method called Dynamic-Choice-Pessimistic-Policy-Optimization (DCPPO). It does not provide recent papers on RL with human feedback. |
| The provided paper is about offline Reinforcement Learning with Human Feedback (RLHF) and proposes a method called Dynamic-Choice-Pessimistic-Policy-Optimization (DCPPO). It does not provide recent papers on reinforcement learning with human feedback. |
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