Results for "policy"

Learning from data generated by a different policy.

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

Systematic review of model/data processes to ensure performance, fairness, security, and policy compliance.

Stress-testing models for failures, vulnerabilities, policy violations, and harmful behaviors before release.

Combines value estimation (critic) with policy learning (actor).

Legal or policy requirement to explain AI decisions.

Strategy mapping states to actions.

Optimizing policies directly via gradient ascent on expected reward.

Learning only from current policy’s data.

Directly optimizing control policies.