Multi-Agent Path Finding with Deadlines
Authors: Hang Ma, Glenn Wagner, Ariel Felner, Jiaoyang Li, T. K. Satish Kumar, Sven Koenig
IJCAI 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our empirical results demonstrate that these MAPF-DL solvers scale well and each one dominates the other ones in different scenarios. |
| Researcher Affiliation | Collaboration | Hang Ma1, Glenn Wagner2, Ariel Felner3, Jiaoyang Li1, T. K. Satish Kumar1, Sven Koenig1 1 University of Southern California 2 CSIRO 3 Ben-Gurion University |
| Pseudocode | Yes | Algorithm 1: High Level of CBS-DL (and MA-DBS); Algorithm 2: High Level of DBS |
| Open Source Code | No | The paper does not provide an explicit statement about the availability of its source code or a link to a code repository for the implemented methods. |
| Open Datasets | No | The paper describes generating its own problem instances for experiments, rather than using a publicly available dataset with a specified access method like a URL or citation. It states: 'We experimented on instances where the start and goal vertices of each agent are placed randomly... Specifically, we use three sets of randomly generated MAPF-DL instances... We generate 50 MAPF-DL instances for each number of agents for each set.' |
| Dataset Splits | No | The paper describes generating random problem instances for evaluation and running all algorithms on them, but it does not specify a training/validation/test split for these instances in the conventional machine learning sense. |
| Hardware Specification | Yes | In this section, we describe our experimental results on a 2.50 GHz Intel Core i5-2450M laptop with 6 GB RAM. |
| Software Dependencies | Yes | The ILP-based algorithm uses CPLEX V12.7.1 [IBM, 2011] as the ILP solver. |
| Experiment Setup | Yes | The start and goal vertices of each agent are randomly placed at distance 48, 49, or 50 for SMALL, 98, 99, or 100 for MEDIUM, and 148, 149, or 150 for LARGE. Each algorithm is given a time limit of 60 seconds to solve each instance. |