Compositional Policy Priors
This paper describes a probabilistic framework for incorporating structured inductive biases into reinforcement learning. These inductive biases arise from policy priors, probability distributions over optimal policies. Borrowing recent ideas from computational linguistics and Bayesian nonparametric...
Main Authors: | Wingate, David, Diuk, Carlos, O'Donnell, Timothy, Tenenbaum, Joshua, Gershman, Samuel |
---|---|
Other Authors: | Joshua Tenenbaum |
Published: |
2013
|
Online Access: | http://hdl.handle.net/1721.1/78573 |
Similar Items
-
Bayesian Policy Search with Policy Priors
by: Wingate, David, et al.
Published: (2014) -
Nonparametric Bayesian Policy Priors for Reinforcement Learning
by: Doshi-Velez, Finale P., et al.
Published: (2011) -
Probing the compositionality of intuitive functions
by: Schulz, Eric, et al.
Published: (2016) -
The causes and consequences explicit in verbs
by: Tenenbaum, Joshua B., et al.
Published: (2015) -
Compositional inductive biases in function learning
by: Schulz, Eric, et al.
Published: (2021)