Reward Model

A neural network trained to predict scalar reward values from state-action pairs or trajectory segments, typically trained on human preferences or expert demonstrations. Reward models replace hand-engineered reward functions with learned ones. They are central to RLHF-style training and are used in robotics to specify complex task objectives that are hard to formalize mathematically.

See this in practice: our real-world evals →