Reinforcement Learning in Robotics

Reinforcement Learning from Human Feedback (RLHF) is a method that improves AI systems by incorporating human evaluations of their outputs. Humans assess AI responses for quality, safety, and alignment, providing feedback that guides the model's learning process. This approach enhances the AI’s ability to generate more accurate, safe, and human-aligned responses, addressing ethical and safety concerns.