Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The Shift Toward Open and Reproducible AI Research," Under Review, 2026. doi: 10.48550/arXiv.2606.16974..
From Qualitative to Quantitative Dominance Pruning for Optimal Planning
Authors: Álvaro Torralba
IJCAI 2017 | Venue PDF | LLM Run Details | Input Tokens: 19,872 Total number of tokens sent to the LLM as input for this paper's analysis. | Output Tokens: 4,198 Total number of tokens produced by the LLM (including reasoning/thinking tokens) for this paper's analysis.
| 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 EMAIL |
| 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). |