Published December 19, 2023 | Version v2
Software Open

Source code for "Learning Domain-Independent Heuristics for Grounded and Lifted Planning" at AAAI-24

  • 1. ROR icon Australian National University
  • 2. ROR icon Laboratory for Analysis and Architecture of Systems

Description

Source code for the AAAI-24 publication "Learning Domain-Independent Heuristics for Grounded and Lifted Planning" by Dillon Z. Chen, Sylvie Thiébaux, and Felipe Trevizan.

 

This archive contains the code for the experiments run for the publication. Up-to-date code can be tracked in the GitHub repository.

 

Acknowledgements:

The authors would like to thank the reviewers and Rostislav Horčík for their comments. The computational resources for this project were partially provided by the Australian Government through the National Computational Infrastructure (NCI) under the ANU Startup Scheme. This work was supported by Australian Research Council grant DP220103815, by the Artificial and Natural Intelligence Toulouse Institute (ANITI), and by the European Union’s Horizon Europe Research and Innovation program under the grant agreement TUPLES No. 101070149.

Files

goose-zenodo-aaai24.zip

Files (86.2 MB)

Name Size Download all
md5:cef88fbeb677911861c5f0b48af8f9c2
86.2 MB Preview Download