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Dong-Sheng Hou

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#artificial intelligence Preprint Aug 2026

BCPPO: Bachelier-Inspired Constrained Proximal Policy Optimization for Tail-Risk-Aware Safe Reinforcement Learning

BCPPO (Bachelier-Inspired Constrained Proximal Policy Optimization), a proximal policy optimization (PPO) method, supports a practical balance among reward, caution around cost predictions that vary across trained critics, and policy-only deployment.

Dong-Sheng Hou, Yanqiao Chen, Yu-Han Rui · 0 citations