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 [1].
Efficient Budgeted Graph Search
Authors: Jasmeet Kaur, Nathan R. Sturtevant
IJCAI 2022 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experimental results validate the performance of BGSe on a range of theoretical and practical problem instances. |
| Researcher Affiliation | Academia | Jasmeet Kaur1 , Nathan R. Sturtevant1,2 1Department of Computing Science, University of Alberta, Canada 2Alberta Machine Intelligence Institute (Amii) EMAIL, EMAIL |
| Pseudocode | Yes | Algorithm 1 A (costl, rel, nl) |
| Open Source Code | Yes | We used the C++ code from the open-source HOG2 repository1 for the baseline algorithms and testing. Our code for BGSe that is used to run these experiments is available in the same repository. 1https://github.com/nathansttt/hog2/tree/PDB-refactor |
| Open Datasets | Yes | In these experiments we test problems from Dragon Age: Origins [Sturtevant, 2012] with the octile heuristic to measure the difference between A*, BGS, and BGSe. |
| Dataset Splits | No | The paper mentions testing on 'problems from Dragon Age: Origins' and 'all problems in the map den601d', but it does not specify explicit training, validation, or test dataset splits (e.g., percentages or sample counts). |
| Hardware Specification | Yes | All experiments are run on a 3.4Ghz Intel Core i7 machine with 16GB of RAM. |
| Software Dependencies | No | The paper mentions using 'C++ code from the open-source HOG2 repository' but does not provide specific version numbers for C++ compilers, HOG2, or any other critical software dependencies. |
| Experiment Setup | Yes | The value of parameters c1, c2, and γ are 2, 8, and 2 respectively for all experiments. For BGSe, we used a re-expansion budget of 1*budget in this case. |