Analyzing Tie-Breaking Strategies for the A* Algorithm

Authors: Augusto B. Corrêa, André G. Pereira, Marcus Ritt

IJCAI 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental We experimentally analyze the performance of A using several tie-breaking strategies on domains from the IPC and zero-cost domains. Our best strategy solves significantly more instances than the standard method in the literature and more than the previous state-of-the-art strategy.
Researcher Affiliation Academia 1 University of Basel, Switzerland 2 Federal University of Rio Grande do Sul, Brazil
Pseudocode No The paper does not contain any pseudocode or clearly labeled algorithm blocks.
Open Source Code No The paper mentions using 'revision 6251 of the Fast-Downward planning system [Helmert, 2006] with the modifications of Asai and Fukunaga (2017)', but does not state that the authors' own modifications or new code are open-source or provide a link.
Open Datasets Yes In total, we used 1104 instances from the IPC and 620 from the zero-cost benchmarks of Asai and Fukunaga (2017).
Dataset Splits No The paper mentions using subsets of the IPC and zero-cost domains and imposing time and memory limits for experiments, but it does not provide specific train, validation, or test dataset splits or percentages.
Hardware Specification Yes All experiments have been run on a PC with an AMD FX-8150 processor running at 3.6 GHz and 32 GB of main memory.
Software Dependencies Yes The experiments use revision 6251 of the Fast-Downward planning system [Helmert, 2006] with the modifications of Asai and Fukunaga (2017).
Experiment Setup Yes In this experiment we have imposed limits of 4 GB and 5 min for each run, following Asai and Fukunaga (2017). For these experiments we use a time limit of 30 minutes, a memory limit of 4 GB.