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; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in [1]
Enhanced Partial Expansion A*
Authors: M. Goldenberg, A. Felner, R. Stern, G. Sharon, N. Sturtevant, R. C. Holte, J. Schaeffer
JAIR 2014 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experimental studies show significant improvements in run-time and memory performance for several standard benchmark applications. |
| Researcher Affiliation | Academia | Meir Goldenberg EMAIL Ariel Felner EMAIL Roni Stern EMAIL Guni Sharon EMAIL Ben-Gurion University of the Negev Beer-Sheva, Israel Nathan Sturtevant EMAIL The University of Denver, Denver, USA Robert C. Holte EMAIL Jonathan Schaeffer EMAIL The University of Alberta Edmonton, Canada |
| Pseudocode | Yes | Procedure 1 A*, PEA* and EPEA*. Procedure 2 IDA* and EPEIDA*. Procedure 3 Algorithmic component of an additive PDBs-based OSF for MAPF. |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described by the authors. While it mentions using Korf's IDA* code, it does not offer the authors' implementation of EPEA* or EPEIDA*. |
| Open Datasets | Yes | Optimal solutions to random instances of the 15-puzzle were first found by Korf (1985) using IDA* and the MD heuristic. Korf has graciously made this code available to the public. The pancake puzzle (Dweighter, 1975). Rubik s Cube was invented in 1974 by Erno Rubik of Hungary. |
| Dataset Splits | No | The paper focuses on combinatorial search problems, where experiments are run on problem 'instances' (e.g., 100 random instances for the 15-puzzle, pancake puzzle, Rubik's cube, or 1,000 generated instances for MAPF). The concept of training/test/validation splits, as typically found in machine learning contexts, is not applicable or explicitly provided for these search problem instances. |
| Hardware Specification | Yes | The timing results were obtained on Dell Optiplex 760. |
| Software Dependencies | No | The paper mentions using "Korf's IDA* code" for the 15-puzzle experiments, but it does not specify any version numbers for this or any other software components used in their methodology. |
| Experiment Setup | Yes | All algorithmic variants were run under the ID framework as described in the footnote. All variants were given up to two minutes and two gigabytes of memory per instance. |