TY - GEN
T1 - Online Multi-Agent Path Finding
T2 - New Results.
AU - Morag, Jonathan
AU - Felner, Ariel
AU - Stern, Roni
AU - Atzmon, Dor
AU - Boyarski, Eli
N1 - DBLP License: DBLP's bibliographic metadata records provided through http://dblp.org/ are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.
PY - 2022/7/17
Y1 - 2022/7/17
N2 - Online MAPF extends the classical Multi-Agent Path Find ingproblem (MAPF) by considering a more realistic problem in which new agents may appear over time. As online solvers arenot aware of which agents will join in the future, the notion of snapshot-optimal was defined, where only current knowledge is considered. In this paper, we perform an extensive com-parison between oracle-optimal solutions (where the solver is preinformed of future agents), snapshot-optimal solutions, and suboptimal solutions obtained by prioritised planning
AB - Online MAPF extends the classical Multi-Agent Path Find ingproblem (MAPF) by considering a more realistic problem in which new agents may appear over time. As online solvers arenot aware of which agents will join in the future, the notion of snapshot-optimal was defined, where only current knowledge is considered. In this paper, we perform an extensive com-parison between oracle-optimal solutions (where the solver is preinformed of future agents), snapshot-optimal solutions, and suboptimal solutions obtained by prioritised planning
KW - Analysis Of Search Algorithms
KW - Continuous Problem Solving
KW - Combinatorial optimization
U2 - https://doi.org/10.1609/socs.v15i1.21772
DO - https://doi.org/10.1609/socs.v15i1.21772
M3 - Conference contribution
SP - 229
EP - 233
BT - Proceedings of the Fifteenth International Symposium on Combinatorial Search (SoCS2022)229
ER -