What is the problem being addressed?
The authors address the problem of finding recursively optimal policies through methods for hierarchical reinforcement learning (HRL) that are general-purpose, support non-hierarchical execution, preserve the markovian property of subtasks involved, and are not adversely affected by state abstractions.