2020
Learning Hierarchical Task Networks with Preferences from Unannotated Demonstrations
CoRL 2020
We address the problem of learning Hierarchical Task Networks (HTNs) from unannotated task demonstrations, while retaining action execution preferences present in the demonstration data. We show that the problem of learning a complex HTN structure can be made analogous to the problem of series/paral