Task diversity produces systematic transfer but inhibits continual reinforcement learning 事件

Task diversity produces systematic transfer but inhibits continual reinforcement learning arXiv:2606.00880v1 Announce Type: cross Abstract: Continual reinforcement learning aims to produce agents that learn not only to improve at their current tasks but also to adapt as task distributions change. Training an agent on many diverse tasks can induce zero-shot generalization, but previous work generally evaluates this generalization after training -- with frozen weights. Whether task diversity also