Heuristics and Symmetries in Classical Planning

Authors: Alexander Shleyfman, Michael Katz, Malte Helmert, Silvan Sievers, Martin Wehrle

AAAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical We investigate the symmetry properties of existing heuristics and reveal that many of them are invariant under symmetries.
Researcher Affiliation Collaboration Alexander Shleyfman Technion, Haifa, Israel alesh@tx.technion.ac.il Michael Katz IBM Haifa Research Lab, Israel katzm@il.ibm.com Malte Helmert and Silvan Sievers and Martin Wehrle University of Basel, Switzerland {malte.helmert,silvan.sievers,martin.wehrle}@unibas.ch
Pseudocode No The paper does not contain any sections labeled 'Pseudocode' or 'Algorithm'. It provides mathematical equations for defining heuristics, but these are not formatted as pseudocode blocks.
Open Source Code No The paper does not provide any statements about releasing source code or links to a code repository for the methodology described.
Open Datasets No The paper is theoretical and does not involve training models on datasets. Therefore, no information on public dataset availability for training is provided.
Dataset Splits No The paper is theoretical and does not involve empirical validation on datasets. Therefore, no information on dataset splits for validation is provided.
Hardware Specification No The paper is theoretical and does not describe any computational experiments. Therefore, no hardware specifications are mentioned.
Software Dependencies No The paper does not mention any specific software dependencies with version numbers. It references existing tools like BLISS (Junttila and Kaski 2007) but not as software dependencies for its own work.
Experiment Setup No The paper is theoretical and does not describe any experimental setup, hyperparameters, or training configurations.