Software Open Access

Code and data for the ICAPS 2022 paper "New Refinement Strategies for Cartesian Abstractions"

David Speck; Jendrik Seipp

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.
Files (231.9 MB)
Name Size
speck-seipp-icaps2022-benchmarks.zip
md5:391395cf8e35c93b34d5eefaf5d98262 		22.5 MB Download
speck-seipp-icaps2022-code.zip
md5:5c4447ede33364cbdbd90777f0f93ed4 		3.6 MB Download
speck-seipp-icaps2022-data.zip
md5:3b22de09df57226ee6382ee5c5c6c7e9 		203.2 MB Download
speck-seipp-icaps2022-reports.zip
md5:ef18575691826b03ef4729511cd29799 		2.5 MB Download
speck-seipp-icaps2022-scripts.zip
md5:a07aa60e085fe1f41c25cbba2250fb1f 		6.4 kB Download
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Publication date:
March 24, 2022
DOI:
10.5281/zenodo.6381925

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Keyword(s):
Classical Planning Heuristic Search Counterexample-Guided Abstraction Refinement
Grants:
European Commission:
  • TAILOR - Foundations of Trustworthy AI - Integrating Reasoning, Learning and Optimization (952215)
License (for files):
GNU General Public License v3.0 or later

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