Published March 12, 2021 | Version 1
Software Open

Code, benchmarks and experiment data for the ICAPS 2021 paper "Dantzig-Wolfe Decomposition for Cost Partitioning"

  • 1. University of Basel
  • 2. Linköping University


This bundle contains code, data and benchmarks for reproducing all experiments reported in the paper. contains the implementation, which is based on Fast Downward 20.06.

pommerening-et-al-icaps2021-scripts.tar.gz contains experiment scripts compatible with Lab 6.3 for reproducing all experiments of the paper.

pommerening-et-al-icaps2021-benchmarks.tar.gz contains the benchmarks used in the experiments. It consists of IPC benchmarks used in all optimal sequential tracks of IPCs up to 2018.

pommerening-et-al-icaps2021-data.tar.gz contains the experimental data. The 3 directories without the "-eval" ending contain raw data of the 3 experiments that were performed for the paper. Each of these contain a subdirectory tree structure "runs-*" where each planner run has its own directory. For each run, there are symbolic links to the input PDDL files domain.pddl and problem.pddl (can be resolved by putting the benchmarks directory to the right place), the run log file "run.log" (stdout), possibly also a run error file "run.err" (stderr), the run script "run" used to start the experiment, and a "properties" file that contains data parsed from the log file(s). Directories with the "-eval" ending each contain a "properties" file which contains a JSON directory with combined data of all runs of the corresponding experiment as well as html and tex files which were used to generate the figures and tables in the paper.

Note on license: we chose GPL v3.0 or later mainly because we consider our implementation based on Fast Downward the main contribution of this package, and Fast Downward comes with GPL v3.0.


Files (194.6 MB)

Name Size Download all
12.7 MB Download
810.6 kB Preview Download
181.1 MB Download
3.9 kB Download

Additional details


TAILOR – Foundations of Trustworthy AI - Integrating Reasoning, Learning and Optimization 952215
European Commission
BDE – Beyond Distance Estimates: A New Theory of Heuristics for State-Space Search 817639
European Commission