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Authors: Pavel Surynek 1 ; Jiří Švancara 2 ; Ariel Felner 3 and Eli Boyarski 4

Affiliations: 1 National Institute of Advanced Industrial Science and Technology (AIST) and Charles University, Japan ; 2 Charles University, Czech Republic ; 3 Ben Gurion University, Israel ; 4 Bar-Ilan University, Israel

ISBN: 978-989-758-220-2

Keyword(s): Multi-Agent Path-Finding (MAPF), Independence Detection (ID), Propositional Satisfiability (SAT), Cost Optimality, Makespan Optimality, Sum-of-costs Optimality, SAT Encodings, Path-Finding on Grids.

Related Ontology Subjects/Areas/Topics: Agents ; Artificial Intelligence ; Cooperation and Coordination ; Formal Methods ; Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Mobile Agents ; Planning and Scheduling ; Robot and Multi-Robot Systems ; Simulation and Modeling ; State Space Search ; Symbolic Systems

Abstract: The problem of optimal multi-agent path finding (MAPF) is addressed in this paper. The task is to find optimal paths for mobile agents where each of them need to reach a unique goal position from the given start with respect to the given cost function. Agents must not collide with each other which is a source of combinatorial difficulty of the problem. An abstraction of the problem where discrete agents move in an undirected graph is usually adopted in the literature. Specifically, it is shown in this paper how to integrate independence detection (ID) technique developed for search based MAPF solving into a compilation-based technique that translates the instance of the MAPF problem into propositional satisfiability formalism (SAT). The independence detection technique allows decomposition of the instance consisting of a given number of agents into instances consisting of small groups of agents with no interaction across groups. These small instances can be solved independently and th e solution of the original instance is combined from small solutions eventually. The reduction of the size of instances translated to the target SAT formalism has a significant impact on performance as shown in the presented experimental evaluation. The new solver integrating SAT translation and the independence detection is shown to be state-of-the-art in its class for optimal MAPF solving. (More)

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Paper citation in several formats:
Surynek, P.; Švancara, J.; Felner, A. and Boyarski, E. (2017). Integration of Independence Detection into SAT-based Optimal Multi-Agent Path Finding - A Novel SAT-based Optimal MAPF Solver.In Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-220-2, pages 85-95. DOI: 10.5220/0006126000850095

@conference{icaart17,
author={Pavel Surynek. and Ji\v{r}í Švancara. and Ariel Felner. and Eli Boyarski.},
title={Integration of Independence Detection into SAT-based Optimal Multi-Agent Path Finding - A Novel SAT-based Optimal MAPF Solver},
booktitle={Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2017},
pages={85-95},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006126000850095},
isbn={978-989-758-220-2},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Integration of Independence Detection into SAT-based Optimal Multi-Agent Path Finding - A Novel SAT-based Optimal MAPF Solver
SN - 978-989-758-220-2
AU - Surynek, P.
AU - Švancara, J.
AU - Felner, A.
AU - Boyarski, E.
PY - 2017
SP - 85
EP - 95
DO - 10.5220/0006126000850095

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