Krzysztof Jankowski

Bigger, Regularized, Optimistic: scaling for compute and sample efficient continuous control

Sample efficiency in Reinforcement Learning (RL) has traditionally been driven by algorithmic enhancements. In this work, we demonstrate that scaling can also lead to substantial improvements. We conduct a thorough investigation into the interplay of scaling model capacity and domain-specific RL en…