Nov 16, 2021 · We show how aggregating feedback from multiple trainers improves the total feedback's accuracy and make the collection process easier in two ways.
Nov 16, 2021 · We show how aggregating feedback from multiple trainers improves the total feedback's accuracy and make the collection process easier in two ...
It offers an actionable tool for improving the feedback collection process or modifying the reward function design if needed. We empirically show that our ...
Reinforcement Learning with Feedback from Multiple Humans with Diverse Skills · Department of Computer Science · Department of Engineering Mathematics · Bristol ...
Dec 6, 2021 · Neural Information Processing Systems (NeurIPS) is a multi-track machine learning and computational neuroscience conference that includes ...
People also ask
What is reinforcement learning with human feedback?
What are the different types of feedback in reinforcement learning?
What is the one real world example of reinforcement learning?
What is the primary purpose of a reward model in reinforcement learning with human feedback?
Our method significantly improves over existing preference-based RL algorithms in all tasks when learning from diverse human feedback. Proceedings of the ...
Dive into the research topics of 'Reinforcement Learning with Feedback from Multiple Humans with Diverse Skills'. Together they form a unique fingerprint. Sort ...
A promising approach to improve the robustness and exploration in Reinforcement Learning is collecting human feedback and that way incorporating prior ...
Dec 30, 2023 · Abstract:Reinforcement learning from human feedback (RLHF) emerges as a promising paradigm for aligning large language models (LLMs).
Sep 26, 2024 · Reinforcement Learning (RL) involves training an agent to make a series of decisions by rewarding it for desirable actions. The main components ...