Published March 12, 2023
| Version 2
Software
Open
Code and Data for Learning Hierarchical Policies
- 1. Linköping University
- 2. RWTH Aachen University
Description
Code and data for the paper "Learning Hierarchical Policies by Iteratively Reducing the Width of Sketch Rules"
The archive h-policy-learner.zip contains code and data for learning and testing hierarchical policies
Link to GitHub repository: https://github.com/drexlerd/h-policy-learner
The PDF drexler-et-al-kr2023-extended.pdf is an extended version of the paper with additional proofs.
Notes
Additional Acknowledgements: This work was partially supported by the Wallenberg AI, Autonomous Systems and Software Program (WASP) funded by the Knut and Alice Wallenberg Foundation. - The computations were enabled by resources provided by the Swedish National Infrastructure for Computing (SNIC), partially funded by the Swedish Research Council through grant agreement no. 2018-05973. The computations were enabled by resources provided by the National Academic Infrastructure for Supercomputing in Sweden (NAISS) and the Swedish National Infrastructure for Computing (SNIC) at the the National Supercomputer Centre at Linköping University partially funded by the Swedish Research Council through grant agreements no. 2022-06725 and no. 2018-05973.
Files
drexler-et-al-kr2023-extended.pdf
Files
(887.7 MB)
| Name | Size | Download all |
|---|---|---|
|
md5:6a4ecfdd65fd7ea94965125ea641d778
|
353.4 kB | Preview Download |
|
md5:34c0eeff4f05fdc133e87150ef61b9e2
|
887.4 MB | Preview Download |