Multiagent Stochastic Shortest Path Problem
Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence. Main Track. Pages 163-171.
https://doi.org/10.24963/ijcai.2026/19
Keywords
- Agent-based and Multi-agent Systems: Multi-agent planning
- Agent-based and Multi-agent Systems: Coordination and cooperation
Abstract
We introduce and study the multi-agent stochastic shortest path (MSSP) problem, in which k agents strive to reach a target state, aiming to minimize the expected time to reach the target by any agent. We analyze the computational and strategy-complexity of the problem in both autonomous and coordinated settings, and we design efficient strategy-synthesis algorithms. The algorithms are experimentally evaluated on instances of increasing size against natural baselines.
@inproceedings{ijcai2026p19,
title = {Multiagent Stochastic Shortest Path Problem},
author = {Jonáš, Martin and Kucera, Antonin and Kůr, Vojtěch and Mačák, Jan and Rehak, Vojtech},
booktitle = {Proceedings of the Thirty-Fifth International Joint Conference on
Artificial Intelligence, {IJCAI-26}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Diego Calvanese},
pages = {163--171},
year = {2026},
month = {8},
note = {Main Track},
doi = {10.24963/ijcai.2026/19},
url = {https://doi.org/10.24963/ijcai.2026/19},
}
TY - CPAPER TI - Multiagent Stochastic Shortest Path Problem AU - Jonáš, Martin AU - Kucera, Antonin AU - Kůr, Vojtěch AU - Mačák, Jan AU - Rehak, Vojtech T2 - Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-26 PB - International Joint Conferences on Artificial Intelligence Organization PY - 2026 SP - 163 EP - 171 DO - 10.24963/ijcai.2026/19 UR - https://doi.org/10.24963/ijcai.2026/19 ER -Copied
Machine-readable versions of this paper, for tools and AI agents: