Learned Reward

A reward function that is learned from data (human preferences, demonstrations, or language descriptions) rather than hand-engineered. Reward learning methods include inverse RL, reward modeling from human comparisons (RLHF-style), and VLM-based reward scoring (using CLIP similarity or LLM evaluation). Learned rewards address the challenge that well-shaped manual reward functions are often difficult to specify for complex manipulation tasks.