From Qualitative to Quantitative Dominance Pruning for Optimal Planning

Authors: Álvaro Torralba

IJCAI 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental We run experiments on all the optimal-track STRIPS planning instances from the international planning competitions (IPC 98 IPC 14). All experiments were conducted on a cluster of Intel Xeon E5-2650v3 machines with time (memory) cut-offs of 30 minutes (4 GB).
Researcher Affiliation Academia Alvaro Torralba Saarland University, Saarland Informatics Campus, Saarbr ucken, Germany torralba@cs.uni-saarland.de
Pseudocode Yes Algorithm 1: Quantitative LD simulation
Open Source Code No The paper does not provide an explicit statement or link to open-source code for the methodology described. It refers to a technical report which is a PDF document, not a code repository.
Open Datasets Yes We run experiments on all the optimal-track STRIPS planning instances from the international planning competitions (IPC 98 IPC 14).
Dataset Splits No The paper does not provide specific details on dataset splits (e.g., percentages, sample counts, or explicit mention of train/validation/test sets). It mentions using benchmarks from IPC but no split methodology.
Hardware Specification Yes All experiments were conducted on a cluster of Intel Xeon E5-2650v3 machines with time (memory) cut-offs of 30 minutes (4 GB).
Software Dependencies No The paper mentions using 'M&S with the merge DFP strategy' but does not provide specific version numbers for software dependencies (e.g., programming languages, libraries, or solvers with their versions).
Experiment Setup Yes All experiments were conducted on a cluster of Intel Xeon E5-2650v3 machines with time (memory) cut-offs of 30 minutes (4 GB).