Conditions for Avoiding Node Re-expansions in Bounded Suboptimal Search

Authors: Jingwei Chen, Nathan R. Sturtevant

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

Reproducibility Variable Result LLM Response
Research Type Experimental The experimental results compare priority functions within this class to see if the new priority functions outperform WA*. Several standard domains are used for testing.
Researcher Affiliation Academia Jingwei Chen and Nathan R. Sturtevant Department of Computing Science, University of Alberta, Edmonton, AB Canada {jingwei5,nathanst}@ualberta.ca
Pseudocode Yes Algorithm 1 Generic Best-First Search
Open Source Code No The paper references prior work and experimental results, but does not include any explicit statement about providing open-source code for the methodology described in this paper, nor does it provide a link to such code.
Open Datasets Yes On grid maps we tested on 15,928 problem instances from the Dragon Age: Origins (DAO) map set, 6,444 problem instances from the Star Craft 1 (SC1) map set, and on 35,360 problem instances on maps with 40% random obstacles [Sturtevant, 2012]. The instance are the standard 100 Korf instance [Korf, 1985]. Finally, we followed the heavy variant of pancake puzzle created by Gilon et al. [2016], where the cost of flipping a prefix (V [1] V [i + 1]) is the max(V [1]; V [i + 1]).
Dataset Splits No The paper describes the datasets used and the number of instances, but it does not specify any training, validation, or test splits, nor does it mention cross-validation.
Hardware Specification No The paper does not provide any specific details about the hardware (e.g., CPU, GPU models, memory) used to run the experiments.
Software Dependencies No The paper mentions different algorithms and heuristics used (e.g., WA*, A*epsilon, MD, HGAP heuristic) but does not provide specific software names with version numbers that would be necessary to replicate the experiment environment.
Experiment Setup Yes The experimental results compare priority functions within this class to see if the new priority functions outperform WA*. Several standard domains are used for testing. We experiment with the various weights for WA*, and best-first search with the convex downward parabola (ΦXDP ) and the convex upward parabola (ΦXUP ).