Proofs, Code, and Data for the ICAPS 2022 Paper

This upload contains code and data for learning policy sketches for classical planning domains and comparing the planners (1) first iteration of LAMA, (2) Dual-BFWS, (3) Serialized Iterated Width (SIW), and (4) Serialized Iterated Width with Sketches (SIWR) on a subset of classical planning benchmarks. The upload also contains an extended version of the paper published at ICAPS with further details and proofs. - benchmarks.zip contains a subset of classical planning domains. - experiments.zip contains experimental code and data for learning sketches and testing the four planners from above - data.zip contains textual representation of sketches for some of these domains, which can be given as input to the SIWR planner, and the logs generated when learning policy sketches. - drexler-et-al-icaps2022-extended.pdf is an extended version of the paper published at the 32nd International Conference on Automated Planning and Scheduling (ICAPS2022).Additional Acknowledgements: - This work was partially supported by the Wallenberg AI, Autonomous Systems and Software Program (WASP) funded by the Knut and Alice Wallenberg Foundation. - The computations were enabled by resources provided by the Swedish National Infrastructure for Computing (SNIC), partially funded by the Swedish Research Council through grant agreement no. 2018-0597