Steven Tang

Position: Lifetime tuning is incompatible with continual reinforcement learning

In continual RL we want agents capable of never-ending learning, and yet our evaluation methodologies do not reflect this. The standard practice in RL is to assume unfettered access to the deployment environment for the full lifetime of the agent. For example, agent designers select the best perform…