Parnian Behdin

Position: Deployed Reinforcement Learning should be Continual

Reinforcement Learning (RL) has received increasing attention and adoption in real-world use cases. Most of these systems follow a train-then-fix paradigm, where trained agents do not learn while interacting with the world, until performance degrades and retraining becomes necessary. In this positio…