Code, Benchmarks and Experiment Data for the ICAPS 2023 Paper "Landmark Progression in Heuristic Search"

This is a collection of code, data, and benchmarks for reproducing all experiments reported in the paper. The data is split into *satisficing* and *optimal* elements, stemming from the fact that evaluations were conducted on two separate code basis' (buechner-et-al-icaps2023-code-*.zip contains these implementations based on Fast Downward 20.06).

buechner-et-al-icaps2023-scripts-*.zip contains experiment scripts compatible with Lab 6.2 for reproducing all experiments of the paper.

buechner-et-al-icaps2023-benchmarks.zip contains the benchmarks used in the experiments (both satisficing and optimal). It consists of IPC benchmarks used in all classical tracks of IPCs up to 2018.

buechner-et-al-icaps2023-data-*.zip contains the experimental data. All directories except those ending with"-eval" contain raw data of the 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 bz putting the benchmarks directorz to the right place), the run log file "run.log" (stdout), possibly also a run error file "run.error" (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 dictionary 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 licence: 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.