Hierarchy Through Composition with Multitask LMDPs

By Andrew M. Saxe, Adam Christopher Earle, Benjamin Rosman. 2017

38 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Sergey Levine
2. Pieter Abbeel
3. Chelsea Finn
4. Tuomas Haarnoja
5. Abhishek Gupta
6. Ofir Nachum
7. Yoshua Bengio
8. Tianhe Yu

Citations in the corpus

• Latent Space Policies for Hierarchical Reinforcement Learning (2018, methodology): “…policies with learning of latent spaces (Haarnoja et al., 2017; Hausman et al., 2018) and even with learning hierarchies in small state spaces (Saxe et al., 2017), to our knowledge, our method is the first to extend this mechanism to the setting of learning hierarchical policies with deep RL…”
• The Option Keyboard: Combining Skills in Reinforcement Learning (2021, unknown): “[20] to propose a hierarchical approach.”