arrow
Return

Multi-Agent Path Finding - An Overview

delete2019-10-14
delete63
PRE
AI
R
Roni Stern *
DOI:10.1007/978-3-030-33274-7_6delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
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.
Keywords:
Multi-Agent Pathfinding
Heuristic search

Journal

Artificial Intelligence Review cover
Artificial Intelligence Review
IF:
13.9
Papers:
6.1K
Citations:
1.9W

Organization

B
ben gurion university
Scholars:
1.3W
Papers: 1.0W
Citations: 5
Cited Papers

Cited Papers

Conflict-based search for optimal multi-agent pathfinding
err2015-02-01
err635
PREAI
errSharon, Guni; Stern, Roni; Felner, Ariel; Sturtevant, Nathan R.
errShare
errSave
The increasing cost tree search for optimal multi-agent pathfinding
err2013-02-01
err202
errOAAI
errSharon, Guni; Stern, Roni; Goldenberg, Meir; Felner, Ariel
errShare
errSave
Measurements of DC conductivity of suspensions in non aqueous media
err2009-05-01
err0
PREAI
errManuel Medrano; Carlos Soria-Hoyo; Alberto T. Pérez
errShare
errSave
Thoracic organ transplantation may not increase the risk of bacterial transmission in intensive care units
err2007-03-01
err0
PREAI
errFrauke Mattner; Anna S. Rüden; Lutz Mattner; Iris F. Chaberny; Stefan Ziesing; Martin Strueber; Petra Gastmeier
errShare
errSave
researcher View more