A* variants for optimal multi-agent pathfinding

Meir Goldenberg; Ariel Felner; Roni Stern; Guni Sharon; Jonathan Schaeffer

A* variants for optimal multi-agent pathfinding

Meir Goldenberg, Ariel Felner, Roni Stern, Guni Sharon, Jonathan Schaeffer

Research output: Contribution to conference › Paper › peer-review

Abstract

Several variants of A* have been recently proposed for finding optimal solutions for the multi-agent pathfinding (MAPF) problem. However, these variants have not been deeply compared either quantitatively or qualitatively. In this paper we aim to fill this gap. In addition to obtaining a deeper understanding of the existing algorithms, we describe in detail the application of the new enhanced partial-expansion technique to MAPF and show how pattern databases can be applied on top of this technique.

Original language	American English
Pages	19-25
Number of pages	7
State	Published - 1 Dec 2012
Event	2012 AAAI Workshop - Toronto, ON, Canada Duration: 22 Jul 2012 → 22 Jul 2012

Conference

Conference	2012 AAAI Workshop
Country/Territory	Canada
City	Toronto, ON
Period	22/07/12 → 22/07/12

All Science Journal Classification (ASJC) codes

General Engineering

Cite this

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title = "A* variants for optimal multi-agent pathfinding",

abstract = "Several variants of A* have been recently proposed for finding optimal solutions for the multi-agent pathfinding (MAPF) problem. However, these variants have not been deeply compared either quantitatively or qualitatively. In this paper we aim to fill this gap. In addition to obtaining a deeper understanding of the existing algorithms, we describe in detail the application of the new enhanced partial-expansion technique to MAPF and show how pattern databases can be applied on top of this technique.",

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T1 - A* variants for optimal multi-agent pathfinding

AU - Goldenberg, Meir

AU - Felner, Ariel

AU - Stern, Roni

AU - Sharon, Guni

AU - Schaeffer, Jonathan

PY - 2012/12/1

Y1 - 2012/12/1

N2 - Several variants of A* have been recently proposed for finding optimal solutions for the multi-agent pathfinding (MAPF) problem. However, these variants have not been deeply compared either quantitatively or qualitatively. In this paper we aim to fill this gap. In addition to obtaining a deeper understanding of the existing algorithms, we describe in detail the application of the new enhanced partial-expansion technique to MAPF and show how pattern databases can be applied on top of this technique.

AB - Several variants of A* have been recently proposed for finding optimal solutions for the multi-agent pathfinding (MAPF) problem. However, these variants have not been deeply compared either quantitatively or qualitatively. In this paper we aim to fill this gap. In addition to obtaining a deeper understanding of the existing algorithms, we describe in detail the application of the new enhanced partial-expansion technique to MAPF and show how pattern databases can be applied on top of this technique.

UR - http://www.scopus.com/inward/record.url?scp=84875578209&partnerID=8YFLogxK

M3 - Paper

SP - 19

EP - 25

T2 - 2012 AAAI Workshop

Y2 - 22 July 2012 through 22 July 2012

ER -

A* variants for optimal multi-agent pathfinding

Abstract

Conference

All Science Journal Classification (ASJC) codes

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