IJCAI 2023poster10 citations

In Which Graph Structures Can We Efficiently Find Temporally Disjoint Paths and Walks?

Pascal Kunz, Hendrik Molter, Meirav Zehavi

Abstract

A temporal graph has an edge set that may change over discrete time steps, and a temporal path (or walk) must traverse edges that appear at increasing time steps. Accordingly, two temporal paths (or walks) are temporally disjoint if they do not visit any vertex at the same time. The study of the computational complexity of finding temporally disjoint paths or walks in temporal graphs has recently been initiated by Klobas et al.. This problem is motivated by applications in multi-agent path finding (MAPF), which include robotics, warehouse management, aircraft management, and traffic routing. We extend Klobas et al.’s research by providing parameterized hardness results for very restricted cases, with a focus on structural parameters of the so-called underlying graph. On the positive side, we identify sufficiently simple cases where we can solve the problem efficiently. Our results reveal some surprising differences between the “path version” and the “walk version” (where vertices may be visited multiple times) of the problem, and answer several open questions posed by Klobas et al.

Agent-based and Multi-agent Systems: MAS: Multi-agent planningPlanning and Scheduling: PS: Routing
BibTeX
@inproceedings{ijcai2023p21,
  title     = {In Which Graph Structures Can We Efficiently Find Temporally Disjoint Paths and Walks?},
  author    = {Kunz, Pascal and Molter, Hendrik and Zehavi, Meirav},
  booktitle = {Proceedings of the Thirty-Second International Joint Conference on
               Artificial Intelligence, {IJCAI-23}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Edith Elkind},
  pages     = {180--188},
  year      = {2023},
  month     = {8},
  note      = {Main Track},
  doi       = {10.24963/ijcai.2023/21},
  url       = {https://doi.org/10.24963/ijcai.2023/21},
}
In Which Graph Structures Can We Efficiently Find Temporally Disjoint Paths and Walks? · IJCAI 2023