This paper focuses on finding optimal solutions to the multiagent path finding (MAPF) problem over undirected graphs where the task is to find non-colliding paths for multiple agents, each with a different start and goal position. An encoding of MAPF to Boolean satisfiability (SAT) is already known to the makespan optimal variant of the problem. In this paper we present the first SAT-solver for minimizing the sum of costs enabled by introducing cardinality constraints into the SAT encoding. An experimental evaluation on grid graphs indicate promising performance of the new SAT-based method in comparison with the best variants of previous sum-of-costs search solvers.
|Title of host publication||AAMAS 2016 - Proceedings of the 2016 International Conference on Autonomous Agents and Multiagent Systems|
|Publisher||International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)|
|Number of pages||2|
|State||Published - 2016|
|Event||15th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2016 - Singapore, Singapore|
Duration: 9 May 2016 → 13 May 2016
|Name||Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS|
|Conference||15th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2016|
|Period||9/05/16 → 13/05/16|
Bibliographical notePublisher Copyright:
Copyright © 2016, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.
- Boolean satisfiability (SAT)
- Makespan objective
- Multi-agent path finding (MAPF)
- Sum of costs objective