v1.0.1

Clean re-implementation of GOOSE with the WLPlan package. New features include:

• support for classical grounded, classical lifted, and numeric planning
• new ranking formulations
• Apptainer image
• PCA visualisations of training data

Furthermore, support for GNNs is deprecated as they are inferior to WL learned heuristics. We refer to previous releases for GNN implementations.

NeurIPS-24

Source code for the NeurIPS-24 publication "Graph Learning for Numeric Planning" by Dillon Z. Chen and Sylvie Thiébaux

ICAPS-24

Source code for the ICAPS-24 publication "Return to Tradition: Learning Reliable Heuristics with Classical Machine Learning" by Dillon Z. Chen, Felipe Trevizan, and Sylvie Thiébaux

AAAI-24

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