Learning Transferable Skills using Goal-Conditioned Bisimulation
The method addresses limitations in unsupervised skill discovery by learning action-aware temporal representations that ensure functional equivariance and using goal-conditioned bisimulation. This enables the discovery of transferable skills robust to layout variations by conditioning skill behavior only on relevant state features, leading to better generalization across different environments.