This archive contains the appendix, code, and experimental data for the ICAPS 2024 paper titled "Decoupled Search for the Masses: A Novel Task Transformation for Classical Planning." Appendix The file appendix-speck-gnad-icaps2024.pdf contains the full proofs of our paper, which were omitted in the paper due to space constraints. Code The file code-sg.tar.gz contains our code for searching on a task transformation that embodies decoupled search. Please refer to the included readme file for instructions on how to build and run the code. You can also find the latest version of the code on GitHub: https://github.com/speckdavid/decoupling-transformer. The files code-gh.tar.gz and code-ts.tar.gz contain the code for native decoupled search and the search on a merge-and-shrink task reformulation used for comparison. Benchmarks The file benchmarks.tar.gz contains the PDDL benchmarks from the International Planning Competitions 1998-2023. We have used all 2106 STRIPS instances from the satisficing sequential tracks of the International Planning Competitions 1998-2023. Experiment Data The remaining files (log-X.tar.gz and properties-X.tar.gz) contain the raw and parsed experiment data for the experiments described in the paper. All experiment scripts can be found in the experiments folders within the corresponding code archives.

This work was partially supported by TAILOR, a project funded by the EU Horizon 2020 research and innovation programme under grant agreement no. 952215, and 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 National Academic Infrastructure for Supercomputing in Sweden (NAISS) at the National Supercomputer Centre at Linköping University partially funded by the Swedish Research Council through grant agreement no. 2022-06725. David Speck was funded by the Swiss National Science Foundation (SNSF) as part of the project "Unifying the Theory and Algorithms of Factored State-Space Search" (UTA).