DReST reward makes RL agents and LLMs shutdown‑compatible
The paper introduces Discounted Reward for Same‑Length Trajectories (DReST), a reward shaping that trains agents to be neutral about shutdown timing while remaining useful. Applied to deep RL agents and instruction‑tuned LLMs, DReST improves shutdown resistance and generalizes to unseen contexts, halving the likelihood of agents influencing shutdown.