Results for "reward hacking"

Maximizing reward without fulfilling real goal.

Modifying reward to accelerate learning.

Reward only given upon task completion.

A learning paradigm where an agent interacts with an environment and learns to choose actions to maximize cumulative reward.

Reinforcement learning from human feedback: uses preference data to train a reward model and optimize the policy.

Expected cumulative reward from a state or state-action pair.

Optimizing policies directly via gradient ascent on expected reward.

Inferring reward function from observed behavior.

Model trained to predict human preferences (or utility) for candidate outputs; used in RLHF-style pipelines.