LaCAM: Search-Based Algorithm for Quick Multi-Agent Pathfinding

Authors: Keisuke Okumura

AAAI 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental Our exhaustive experiments reveal that La CAM is comparable to or outperforms state-of-the-art sub-optimal MAPF algorithms in a variety of scenarios, regarding success rate, planning time, and solution quality of sum-of-costs.
Researcher Affiliation Academia Keisuke Okumura Tokyo Institute of Technology Tokyo, Japan okumura.k@coord.c.titech.ac.jp
Pseudocode Yes Algorithm 1 shows an example implementation of La CAM.
Open Source Code Yes La CAM was coded in C++, available in the online supplementary material.
Open Datasets Yes Next, we tested La CAM using the MAPF benchmark (Stern et al. 2019), which includes a set of four-connected grids and start goal pairs for agents.
Dataset Splits No The paper mentions using '25 random scenarios' from the MAPF benchmark but does not specify a distinct validation split or any explicit train/validation/test splits for reproducibility.
Hardware Specification Yes The experiments were run on a desktop PC with Intel Core i9-7960X 2.8 GHz CPU and 64 GB RAM.
Software Dependencies No The paper states 'La CAM was coded in C++' and mentions using 'implementations coded by their respective authors' for baselines, but it does not provide specific version numbers for any libraries, frameworks, or compilers used.
Experiment Setup Yes The runtime limit was set to 30 s following (Stern et al. 2019). La CAM was run five times for each setting. The runtime limit was set to 1000 s. ... The agent order of the initial high-level node was in descending order of the distance between the start and goal... In other high-level nodes... we prioritized agents who are not on their goal...