Front-to-End Bidirectional Heuristic Search with Near-Optimal Node Expansions
Authors: Jingwei Chen, Robert C. Holte, Sandra Zilles, Nathan R. Sturtevant
IJCAI 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experimental results show that NBS competes with or outperforms existing bidirectional search algorithms, and often outperforms A* as well. |
| Researcher Affiliation | Academia | Jingwei Chen University of Denver Denver, CO, USA jingchen@cs.du.edu; Robert C. Holte University of Alberta Edmonton, AB, Canada rholte@ualberta.ca; Sandra Zilles University of Regina Regina, SK, Canada zilles@uregina.ca; Nathan R. Sturtevant University of Denver Denver, CO, USA sturtevant@cs.du.edu |
| Pseudocode | Yes | The pseudocode for NBS is shown in Algorithms 1 and 2. [...] Algorithm 3 NBS pseudocode for selecting the best pair from Open list. |
| Open Source Code | No | The paper does not provide any statement or link indicating the public availability of the source code for the described methodology. |
| Open Datasets | Yes | In Table 1 we present results on problems from four different domains, including grid-based pathfinding problems [Sturtevant, 2012] ( brc maps from Dragon Age: Origins (DAO)), random 4-peg Tower of Hanoi (TOH) problems, random pancake puzzles, and the standard 15 puzzle instances [Korf, 1985]. |
| Dataset Splits | No | The paper mentions using standard benchmark problems but does not explicitly provide specific details on training, validation, and test dataset splits (e.g., percentages, counts, or explicit standard split names). |
| Hardware Specification | No | The paper does not provide specific details on the hardware (e.g., CPU, GPU models, memory) used to run the experiments. |
| Software Dependencies | No | The paper does not list specific software dependencies with version numbers (e.g., programming languages, libraries, frameworks) used in the experiments. |
| Experiment Setup | No | The paper does not provide specific experimental setup details such as concrete hyperparameter values, training configurations, or system-level settings used in the experiments. |