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. 2018-05973