State-Dependent Cost Partitionings for Cartesian Abstractions in Classical Planning
Authors: Thomas Keller, Florian Pommerening, Jendrik Seipp, Florian Geißer, Robert Mattmüller
IJCAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our empirical results give evidence that ignoring the context of actions in the computation of a cost partitioning leads to a significant loss of information. |
| Researcher Affiliation | Academia | University of Basel, Switzerland {tho.keller, florian.pommerening, jendrik.seipp}@unibas.ch Florian Geißer and Robert Mattm uller University of Freiburg, Germany {geisserf, mattmuel}@informatik.uni-freiburg.de |
| Pseudocode | No | The paper describes algorithms and processes, but does not include any formal pseudocode blocks or algorithm listings. |
| Open Source Code | No | The paper states 'We have implemented the saturated state-dependent cost partitioning algorithm that is sketched in the previous section on top of the CEGAR implementation of Seipp and Helmert [2013] in the Fast Downward planning system [Helmert, 2006].' This refers to third-party systems that were used, but there is no explicit statement or link indicating that the authors' own code for their methodology is open-sourced. |
| Open Datasets | Yes | We have performed experiments on all supported IPC 1998 2014 benchmarks on Intel Xeon E5-2660 CPUs running at 2.2 GHz with a time limit of 30 minutes and a memory limit of 2 GB. |
| Dataset Splits | No | The paper mentions using 'IPC 1998 2014 benchmarks' but does not specify any training, validation, or test dataset splits. The term 'validation' in the paper refers to the general concept of ensuring admissibility or theoretical properties, not a dataset split. |
| Hardware Specification | Yes | We have performed experiments on all supported IPC 1998 2014 benchmarks on Intel Xeon E5-2660 CPUs running at 2.2 GHz with a time limit of 30 minutes and a memory limit of 2 GB. |
| Software Dependencies | No | The paper mentions 'CEGAR implementation of Seipp and Helmert [2013]' and 'Fast Downward planning system [Helmert, 2006]' but does not provide specific version numbers for these or any other software components. |
| Experiment Setup | Yes | Our algorithms use the same parameter settings as the configuration that performed best for saturated stateindependent cost partitionings in the original work on the topic [Seipp and Helmert, 2014] with two exceptions: first, we used a maximal number of states (10000) instead of a timeout to decide when the heuristic computation terminates in order to make the abstraction generation process deterministic. And second, we do not interleave the generation of an abstraction based on the latest remaining cost function with the computation of its saturated cost function but compute all abstractions with the original cost function instead. |