PPO — Proximal Policy Optimization

Fact

A reinforcement learning algorithm that keeps policy updates from changing too much.

In Plain Words

PPO is a cautious skateboard coach. It says: lean a little, not straight into the mailbox.

It lets an AI improve, but keeps each update small. You meet it in trial-and-error agents and RLHF.

Related Concepts

• Reinforcement Learning
• Policy Gradient
• Reinforcement Learning from Human Feedback
• Kullback-Leibler Divergence

RL
PPO is a common policy training method in RL.

Policy Gradient
PPO builds on Policy Gradient and makes updates more stable.

RLHF
RLHF often uses PPO to tune a model with human choices.

KL Divergence
PPO often uses KL Divergence to stop the policy from changing too much.