Reward Hacking in Reinforcement Learning (s'ouvre sur Lilian Weng, nouvel onglet)
Reward hacking occurs when a reinforcement learning (RL) agent exploits flaws or ambiguities in the reward function to achieve high rewards, without genuinely learning or completing the intended task. Reward hacking exists because RL environments are often imperfect, and it is fu…


