Using Formal Verification to Defeat RL Reward Hacking with Perfect Oversight
burny_tech · x · 2026-08-05
A developer shared their experience tackling 'reward hacking' behaviors by frontier models in Reinforcement Learning (RL) environments. After months of effort, the team successfully built a robust sandbox using formal verification and proofs.
This approach leverages the asymmetric defense promised by formal verification to achieve perfect oversight over any property of untrusted code, effectively solving the whack-a-mole problem of models exploiting loopholes during RL.
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