Concepts & capability filters
proximal policy optimization
PPO is an on-policy reinforcement learning algorithm used in RLHF to update the LLM policy model by maximizing a clipped surrogate objective, ensuring stable training through trust-region constraints.
- Category
- Not classified
- Difficulty
- Not classified
- Aliases
- None tracked
- Last reviewed
- 2026-07-02
Key facts
- It balances reward maximization with KL-divergence penalties to prevent large policy shifts.