Reinforcement Learning from Human Feedback - A Review
Prof. Satya Singh, Ratnesh Kumar Sharma
2024 · Zenodo (CERN European Organization for Nuclear Research)
Reinforcement Learning from Human Feedback (RLHF) is a burgeoning field at the intersection of artificial intelligence and human interaction. This approach involves training models to make decisions in dynamic environments by iteratively receiving feedback from human evaluators. In this process, initial models interact with the environment, and human evaluators provide feedback on the model's actions. The model is then updated based on this feedback, enhancing its decision-making capabilities over time. RLHF is particularly valuable in scenarios where predefine d rules may be inadequate, emph…
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