Hierarchical Reinforcement Learning

@inproceedings{Diuk2009HierarchicalRL,
  title={Hierarchical Reinforcement Learning},
  author={Carlos Diuk and Michael L. Littman},
  booktitle={Encyclopedia of Artificial Intelligence},
  year={2009}
}
Reinforcement learning (RL) deals with the problem of an agent that has to learn how to behave to maximize its utility by its interactions with an environment (Sutton & Barto, 1998; Kaelbling, Littman & Moore, 1996). Reinforcement learning problems are usually formalized as Markov Decision Processes (MDP), which consist of a finite set of states and a… CONTINUE READING