Integrating behavior cloning and reinforcement learning for improved performance in dense and sparse reward environments
This paper investigates how to efficiently transition and update policies, trained initially with
demonstrations, using off-policy actor-critic reinforcement learning. It is well-known that …
demonstrations, using off-policy actor-critic reinforcement learning. It is well-known that …
Attentive multi-task deep reinforcement learning
Sharing knowledge between tasks is vital for efficient learning in a multi-task setting.
However, most research so far has focused on the easier case where knowledge transfer is …
However, most research so far has focused on the easier case where knowledge transfer is …