Proximal Policy Optimization (PPO)
An on-policy reinforcement learning algorithm that restricts step updates to maintain training stability.
PPO optimizes reinforcement learning policies using clipped objective functions. This prevents large, destabilizing updates to model weights, making it a key algorithm for aligning LLMs.
Historical figures and technical concepts for informational purposes only. Not technical, professional, legal, or financial advice. Sources: Official Documentation.