Optimal Any-Angle Pathfinding on a Sphere
Authors: Volodymyr Rospotniuk, Rupert Small
JAIR 2021 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Performance benchmarks are provided for several game maps including Starcraft and Warcraft III as well as for sea navigation on Earth using the NOAA bathymetric dataset. |
| Researcher Affiliation | Industry | Ninety Percent of Everything, Portman House, 2 Portman Street, London, United Kingdom, W1H 6DU |
| Pseudocode | Yes | Algorithm 1: Anya and Spherical Anya Algorithm 2: Successors in Spherical Anya Algorithm 3: Computing a set of adjoint successors Algorithm 4: Intermediate node pruning |
| Open Source Code | No | The paper states "Both algorithms are implemented in Python" but does not provide a specific link to a code repository or an explicit statement about releasing the code for the methodology described. |
| Open Datasets | Yes | Performance benchmarks are provided for several game maps including Starcraft and Warcraft III as well as for sea navigation on Earth using the NOAA bathymetric dataset. NOAA (2009). ETOPO1 earth global relief model. https://www.ngdc.noaa.gov/mgg/global/. |
| Dataset Splits | No | The paper mentions "randomly sampled source and target points" for benchmarks, but it does not specify traditional training/test/validation dataset splits for model development or evaluation, as the work is not machine learning based. |
| Hardware Specification | Yes | Both algorithms are implemented in Python and executed on an AWS EC2 Dual Core Intel Xeon Platinum 8000 R5.Large Instance with 16GB of RAM. |
| Software Dependencies | No | The paper states "Both algorithms are implemented in Python" but does not provide specific version numbers for Python or any libraries used for the implementation. |
| Experiment Setup | No | The paper describes the benchmarking process (e.g., using game maps and random maps, selecting source/target points uniformly), but it does not provide specific hyperparameter values or training configurations in the main text, as the algorithms are deterministic pathfinding algorithms rather than machine learning models requiring such settings. |