Reinforcement Learning · advanced · concept 183 of 311 · Updated Nov 4, 2026
PPO (Proximal Policy Optimization)
For years the default RL algorithm, simpler and more stable than its predecessors, and the method used in the original RLHF pipelines. Newer group-relative variants have largely displaced it for language-model post-training, though PPO remains a standard baseline in robotics and control. Used in RLHF to fine-tune ChatGPT, in robotics, and in game AI. Balances exploration with stable training.
Top AI contributors on this
- Demis HassabisGoogle DeepMind (chair) / Isomorphic Labs
- Pieter AbbeelAmazon / UC Berkeley
- David SilverIneffable Intelligence / UCL
- John SchulmanThinking Machines Lab
- Sergey LevineUC Berkeley / Physical Intelligence
- Chelsea FinnStanford University / Physical Intelligence
Key terms
ClippingTrust regionSurrogate objectiveKL penalty
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