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Code, benchmarks and data for the AAAI 2025 paper "Counting and Reasoning with Plans"

Authors: Speck, David; Hecher, Markus; Gnad, Daniel; Fichte, Johannes; Corrêa, Augusto B.;

Code, benchmarks and data for the AAAI 2025 paper "Counting and Reasoning with Plans"

Abstract

This archive contains the code, benchmarks, and experimental data for the AAAI 2025 paper titled "Counting and Reasoning with Plans". Code The files planalyst.zip, symk.zip, kstar.zip contain the code of the different solvers (references are given in the included Readme file). The different solvers can all be built with Apptainer using the included Apptainer files, and more information on running the solvers is available in the Readme files. Latest version of Planalyst on GitHub: https://github.com/speckdavid/planalyst Benchmarks The file benchmarks.zip contains the PDDL benchmarks from the International Planning Competitions that we used for our experiments. Experiment Data The remaining files (scripts.zip, data.zip, reports.zip) contain the experiment scripts, raw and parsed data, and reports for the experiments described in the paper.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average