Inapproximability of Optimal Multi-Agent Pathfinding Problems
Multi-agent pathfinding MAPF is a problem where multiple autonomous agents must find paths to their respective destinations without colliding. Decisional MAPF on undirected graphs can be solved in polynomial time; Several optimization MAPF variants however are NP-complete. The directed graph variant (diMAPF) is more complex, with its decisional version already being NP-complete. This paper examines the computational approximability of optimal MAPF problems (i.e., minimizing makespan for agent travel distance and maximizing the total number of agents reaching their goals), providing a first set of several inapproximability results for these problems. The results reveal an inherent limitation in approximating optimal solutions for MAPFs, provide a deeper understanding regarding their computational intractability, thus offer foundational references for future research.
Authors
- Alban Grastien (ORCID: https://orcid.org/0000-0001-8466-8777)
- Xing Tan
Institutions
- Lakehead University (CA)
Publication Details
- Journal
- Proceedings of the AAAI Conference on Artificial Intelligence
- Published
- 2025-04-11
- DOI
- https://doi.org/10.1609/aaai.v39i25.34873
- Primary Topic
- Robotic Path Planning Algorithms
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Lakehead University
- Natural Sciences and Engineering Research Council of Canada