Mutex Propagation for SAT-based Multi-Agent Path Finding - Robotics Institute Carnegie Mellon University

Mutex Propagation for SAT-based Multi-Agent Path Finding

Pavel Surynek, Jiaoyang Li, Han Zhang, T. K. Satish Kumar, and Sven Koenig
Conference Paper, Proceedings of 23rd International Conference on Principles and Practice of Multi-Agent Systems (PRIMA '20), pp. 248 - 258, November, 2020

Abstract

Multi-agent path finding (MAPF) is the problem of planning a set of non-colliding paths for a set of agents so that each agent reaches its individual goal location following its path. A mutex from classical planning is a constraint forbidding a pair of facts to be both true or a pair of actions to be executed simultaneously. In the context of MAPF, mutexes are used to rule out the simultaneous occurrence of a pair of agents in a pair of locations, which can prune the search space. Previously mutex propagation had been integrated into conflict-based search (CBS), a major search-based approach for solving MAPF optimally. In this paper, we introduce mutex propagation into the compilation-based (SAT-based) solver MDD-SAT, an alternative to search-based solvers. Our experiments show that, despite mutex propagation being computationally expensive, it prunes the search space significantly so that the overall performance of MDD-SAT is improved.

Notes
The research at the Czech Technical University in Prague was supported by GAČR - the Czech Science Foundation, under grant number 19-17966S. The research at the University of Southern California was supported by National Science Foundation (NSF) under grant numbers 1409987, 1724392, 1817189, 1837779, and 1935712 as well as a gift from Amazon.

BibTeX

@conference{Surynek-2020-131425,
author = {Pavel Surynek and Jiaoyang Li and Han Zhang and T. K. Satish Kumar and Sven Koenig},
title = {Mutex Propagation for SAT-based Multi-Agent Path Finding},
booktitle = {Proceedings of 23rd International Conference on Principles and Practice of Multi-Agent Systems (PRIMA '20)},
year = {2020},
month = {November},
pages = {248 - 258},
}