Multi-agent path finding – an overview

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Multi-Agent Pathfinding (MAPF) is the problem of finding paths for multiple agents such that every agent reaches its goal and the agents do not collide. In recent years, there has been a growing interest in MAPF in the Artificial Intelligence (AI) research community. This interest is partially because real-world MAPF applications, such as warehouse management, multi-robot teams, and aircraft management, are becoming more prevalent. In this overview, we discuss several possible definitions of the MAPF problem. Then, we survey MAPF algorithms, starting with fast but incomplete algorithms, then fast, complete but not optimal algorithms, and finally optimal algorithms. Then, we describe approximately optimal algorithms and conclude with non-classical MAPF and pointers for future reading and future work.

Original languageAmerican English
Title of host publicationArtificial Intelligence - 5th RAAI Summer School, 2019, Tutorial Lectures
EditorsGennady S. Osipov, Aleksandr I. Panov, Konstantin S. Yakovlev
Number of pages20
ISBN (Print)9783030332730
StatePublished - 14 Oct 2019
Event5th RAAI Summer School on Artificial Intelligence, 2019 - Dolgoprudny, Russian Federation
Duration: 4 Jul 20197 Jul 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11866 LNAI


Conference5th RAAI Summer School on Artificial Intelligence, 2019
Country/TerritoryRussian Federation


  • Heuristic search
  • Multi-Agent Pathfinding

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


Dive into the research topics of 'Multi-agent path finding – an overview'. Together they form a unique fingerprint.

Cite this