Code The file speck-seipp-icaps2022-code.zip contains an extended version of the Fast Downward planning system (http://fast-downward.org). Please see http://www.fast-downward.org for detailed instructions on how to compile the planner. Here is the short version for building the planner and running the best performing configuration. The calls for the other configurations can be found in the file speck-seipp-icaps2022-reports.zip. ./build.py ./fast-downward.py PDDL_TASK --search "astar(cegar(subtasks=[original()], max_states=infinity, max_transitions=infinity, max_time=900, pick_split=max_cover, tiebreak_split=max_refined, pick_flaw=min_h_batch_multi_split,max_state_expansions=1000000, use_general_costs=true, debug=false, transform=no_transform(), cache_estimates=true, random_seed=-1))" The latest version of the code is maintained at https://github.com/jendrikseipp/scorpion. Benchmarks The file speck-seipp-icaps2022-benchmarks.zip contains the STRIPS PDDL benchmarks from sequential optimization tracks of IPC 1998-2018. Experiment data The remaining zipfiles contain the raw experiment data, parsed values, scripts and basic reports for the experiments in the paper.

This research was partially supported by TAILOR, a project funded by the EU Horizon 2020 research and innovation programme under grant agreement no. 952215. David Speck was supported by the German Research Foundation (DFG) as part of the EPSDAC project (MA 7790/1-1). Jendrik Seipp was partially supported by the Wallenberg AI, Autonomous Systems and Software Program (WASP) funded by the Knut and Alice Wallenberg Foundation.