BRRL: Bounded Ratio RL Bridges Gap Between Trust Region Theory and PPO's Heuristic Clipping

arXiv·medium signal

Bounded Ratio Reinforcement Learning formally connects trust region optimization theory with the heuristic clipped objective used in PPO, which has a significant theoretical disconnect despite being the dominant on-policy RL algorithm. BRRL introduces a principled regularized and constrained policy optimization framework. Relevant to RLHF/RLVR practitioners who build on PPO for LLM alignment — provides theoretical grounding for ratio-clipping decisions.