SKILL-IL: Disentangling Skill and Knowledge in Multitask Imitation Learning
Bian Xihan,Oscar Mendez,Simon Hadfield,Bian Xihan,Oscar Mendez,Simon Hadfield
In this work, we introduce a new perspective for learning transferable content in multi-task imitation learning. Humans are capable of transferring skills and knowledge. If we can cycle to work and drive to the store, we can also cycle to the store and drive to work. We take inspiration from this and hypothesize the latent memory of a policy network can be disentangled into two partitions. These c...
