Anytime Focal Search with Applications
Authors: Liron Cohen, Matias Greco, Hang Ma, Carlos Hernandez, Ariel Felner, T. K. Satish Kumar, Sven Koenig
IJCAI 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | On the experimental side, we demonstrate the usefulness of AFS for solving hard combinatorial problems, such as the generalized covering traveling salesman problem and the multiagent pathfinding problem. |
| Researcher Affiliation | Academia | Liron Cohen1, Matias Greco2, Hang Ma1, Carlos Hernandez2, Ariel Felner3, T. K. Satish Kumar1 and Sven Koenig1 1University of Southern California 2Universidad Andres Bello 3Ben-Gurion University |
| Pseudocode | Yes | Algorithm 1 presents pseudocode for the unified view of BSS and BCS (blue for BSS and red for BCS). Algorithm 2 presents the pseudocode for AFS. |
| Open Source Code | No | The paper does not provide any specific links or explicit statements about releasing source code for the described methodology. |
| Open Datasets | Yes | We evaluate AFS in the GCTSP domain on benchmark instances from [Shaelaie et al., 2014]. |
| Dataset Splits | No | The paper mentions using "69 medium instances (between 100 and 200 vertices) and 14 large instances (between 535 and 1000 vertices)" but does not specify any training, validation, or test dataset splits or cross-validation methodology. |
| Hardware Specification | No | The paper does not provide specific details about the hardware (e.g., CPU, GPU models, memory) used for running the experiments. |
| Software Dependencies | No | The paper does not provide specific version numbers for any software dependencies or libraries used in the experiments. |
| Experiment Setup | Yes | All runs have a time limit of 100 seconds. All experiments use a 32 32 four-neighbor grid with 20% blocked cells placed randomly. |