"Probabilistic inference for determining options in reinforcement learning."

Christian Daniel et al. (2016)

> Home

Details and statistics

DOI: 10.1007/S10994-016-5580-X

access: open

type: Journal Article

metadata version: 2020-03-02

- view
  - electronic edition via DOI (open access)
  authority control:
- export record
  dblp key:
  - journals/ml/DanielHPN16
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/journals/ml/DanielHPN16
Christian Daniel, Herke van Hoof, Jan Peters, Gerhard Neumann:
Probabilistic inference for determining options in reinforcement learning. Mach. Learn. 104(2-3): 337-357 (2016)

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.