Data for domains without generator for the ICAPS 2021 paper "Automatic Instance Generation for Classical Planning"'



This dataset contains raw data (log files) and parsed data (JSON files) of all planners used in the paper run on planning domains for which there is no generator that could directly be used for the Autoscale training process. This dataset was used to select a subset of tasks as described in the paper, for all Autoscale versions up to this point (Autoscale 21.08 and 21.11). As such, it complements the original Zenodo entry contains the raw experimental data, distributed over a subdirectory for each experiment. 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). contains the parsed data, again distributed over a subdirectory for each experiment. Each contains a "properties" file, which is a JSON file with combined data of all runs of the corresponding experiment. In essence, the properties file is the union over all properties files generated for each individual planner run.
Date made available22 Jun 2022
  • Automatic Instance Generation for Classical Planning

    Torralba, A., Seipp, J. & Sievers, S., 17 May 2021, Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS 21). 1 ed. Palo Alto: AAAI Press, Vol. 31. p. 376-384 9 p. (Proceedings International Conference on Automated Planning and Scheduling, ICAPS).

    Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

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