Limitations of Front-To-End Bidirectional Heuristic Search
Authors: Joseph Barker, Richard Korf
AAAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | In our experiments, we examine the four-peg Towers Of Hanoi problem with arbitrary start and goal states, where we find that bidirectional brute-force search outperforms unidirectional heuristic search. 4 Experiments 4.1 Empirical Studies of Search Spaces |
| Researcher Affiliation | Academia | Joseph K Barker and Richard E Korf {jbarker,korf}@cs.ucla.edu 4732 Boelter Hall Los Angeles, CA 90095 |
| Pseudocode | No | The paper describes algorithms but does not contain structured pseudocode or algorithm blocks (e.g., a figure or section labeled "Algorithm"). |
| Open Source Code | No | The paper does not provide any concrete access information (e.g., specific repository link, explicit code release statement) for source code related to the described methodology. |
| Open Datasets | Yes | We tested seven domains using state-of-the-art heuristics: the 15 Puzzle, the 24 Puzzle, the Pancake Problem, Peg Solitaire, Rubik s Cube, Top Spin, and the four-peg Towers Of Hanoi. |
| Dataset Splits | No | The paper mentions using "random instances" for several problems (e.g., "100 random 15-Puzzle instances", "25 random Rubik s Cube instances") but does not provide specific dataset split information such as exact percentages, sample counts, or cross-validation details for reproduction. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., exact GPU/CPU models, processor types, memory amounts, or detailed computer specifications) used for running its experiments. |
| Software Dependencies | No | The paper mentions algorithms and heuristics used (e.g., "IDA*", "BFHS", "PDBs") but does not provide specific ancillary software details, such as library or solver names with version numbers. |
| Experiment Setup | Yes | We set the cutoff to the optimal solution cost. For the heuristic we considered PDBs of various sizes. We selected the heuristic by solving the first 10 instances with different PDBs and finding the configuration with the best overall performance, which was a partitioning into two PDBs of 15 and 5 disks. |