# PPO Algorithm Line by Line: From Schulman 2017 to InstructGPT — Adapting RL to LLM

> Source: https://sukruyusufkaya.com/en/learn/llm-muhendisligi/ppo-algoritma-satir-satir-schulman-2017
> Updated: 2026-05-13T13:00:29.841Z
> Category: LLM Mühendisliği
> Module: Module 15: Preference Alignment — RLHF, PPO, DPO, GRPO
**TLDR:** Adaptation of Proximal Policy Optimization (Schulman 2017) to LLM RLHF: policy gradient foundation, advantage estimation (GAE), clipped surrogate loss derivation and why 'clip', KL penalty mathematics, value function loss, entropy bonus. InstructGPT's full PPO setup, hyperparameter choices, training stability, debugging strategies.