Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Multi-Agent Path Finding for Large Agents
Authors: Jiaoyang Li,Pavel Surynek,Ariel Felner,Hang Ma,T. K. Satish Kumar,Sven Koenig7627-7634
AAAI 2019 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experimental results show that all MC-CBS variants outperform CBS by up to three orders of magnitude in terms of runtime. |
| Researcher Affiliation | Academia | Jiaoyang Li CS Department Univ. of Southern California EMAIL; Pavel Surynek Faculty of Information Technology Czech Technical University pavel.surynek@fit.cvut.cz; Ariel Felner SISE Department Ben-Gurion University EMAIL; Hang Ma T. K. Satish Kumar Sven Koenig CS Department Univ. of Southern California |
| Pseudocode | Yes | Algorithm 1: A template for Max Weight-d. |
| Open Source Code | No | The paper does not provide any concrete access information (e.g., repository link, explicit statement of code release) for the source code of the methodology described. |
| Open Datasets | Yes | We used a large 4-neighbor 194 x 194 2D grid with 51.3% blocked cells, namely the benchmark game map lak503d from (Sturtevant 2012). |
| Dataset Splits | No | The paper does not provide specific dataset split information (exact percentages, sample counts, citations to predefined splits, or detailed splitting methodology) needed to reproduce the data partitioning into train/validation/test sets. |
| Hardware Specification | Yes | All algorithms were written in C++ and ran on a 2.80 GHz Intel Core i7-7700 laptop with 8 GB RAM and a runtime limit of 5 minutes. |
| Software Dependencies | No | The paper mentions that algorithms were written in C++ and that an off-the-shelf ILP solver was used, but it does not provide specific version numbers for any software components, libraries, or solvers. |
| Experiment Setup | Yes | Each agent is a 2.5 2.5 square whose reference point is its top-left corner. All algorithms use Equation (1) to detect conflicts. All MC-CBS variants use the rectangle constraints discussed in Section 4.3. For MAX, we tested lookahead depths d from 0 to 4. We used 50 instances with randomly generated start vertices and goal vertices for each number of agents. |