One After Another: Learning Incremental Skills for a Changing World

Understand

Reward-free, unsupervised discovery of skills is an attractive alternative to the bottleneck of hand-designing rewards in environments where task supervision is scarce or expensive.

• However, current skill pre-training methods, like many RL techniques, make a fundamental assumption - stationary environments during training.
• Traditional methods learn all their skills simultaneously, which makes it difficult for them to both quickly adapt to changes in the environment, and to not forget earlier skills after such adaptation.
• On the other hand, in an evolving or expanding environment, skill learning must be able to adapt fast to new environment situations while not forgetting previously learned skills.