Regarding Jump Point Search and Subgoal Graphs

Authors: Daniel D. Harabor, Tansel Uras, Peter J. Stuckey, Sven Koenig

IJCAI 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental We run experiments on a large set of standard grid-based pathfinding benchmarks [Sturtevant, 2012] and on the subset of instances from the 2014 Grid-based Path Planning Competition (GPPC).
Researcher Affiliation Academia 1Faculty of Information Technology, Monash University, Melbourne, Australia 2Computer Science Department, University of Southern California, Los Angeles, USA {daniel.harabor, peter.stuckey}@monash.edu, {turas, skoenig}@usc.edu
Pseudocode Yes Algorithm 1: SG connect and JP forward connect.
Open Source Code No The paper states 'Our implementations are based on C++ code from CH-SG [Uras and Koenig, 2018].' but does not explicitly provide concrete access to the source code for the methodology described in this paper.
Open Datasets Yes We run experiments on a large set of standard grid-based pathfinding benchmarks [Sturtevant, 2012] and on the subset of instances from the 2014 Grid-based Path Planning Competition (GPPC).
Dataset Splits No The paper mentions using standard benchmarks from GPPC 2014 and Sturtevant, but does not provide specific dataset split information (exact percentages, sample counts, or detailed splitting methodology) needed to reproduce the data partitioning.
Hardware Specification Yes Our test machine is a 3.6GHz Intel Core i7-7700 CPU with 32GB of RAM.
Software Dependencies No The paper mentions 'C++ code' but does not provide specific version numbers for any ancillary software dependencies like compilers, libraries, or specific tool versions.
Experiment Setup No The paper describes algorithms and high-level implementation details but does not provide specific experimental setup details such as concrete hyperparameter values or training configurations.