Representation Learning Enables Scalable Multitask Deep Reinforcement Learning 事件

Representation Learning Enables Scalable Multitask Deep Reinforcement Learning arXiv:2606.05555v1 Announce Type: cross Abstract: Scaling reinforcement learning (RL) to diverse multitask settings remains a central challenge. While recent advances in model-based RL achieve strong performance, they rely on planning and complex training pipelines, making it unclear which components are essential for scalability. We revisit this question and argue that the primary driver of scalable multitask RL is