Pruning techniques for the increasing cost tree search for optimal multi-agent path finding

Guni Sharon, Roni Stern, Meir Goldenberg, Ariel Felner

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

10 Scopus citations

Abstract

We address the problem of optimal path finding for multiple agents where agents must not collide and their total travel cost should be minimized. Previous work used traditional single-agent search variants of the A* algorithm. In (Sharon et al. 2011) we introduced a novel two-level search algorithm framework for this problem. The high-level searches a novel search tree called increasing cost tree (ICT). The low-level performs a goal test on each ICT node. The new framework, called ICT search (ICTS), showed to run faster than the previous state-of-the-art A* approach by up to three orders of magnitude in many cases. In this paper we focus on the lowlevel of ICTS which performs the goal test. We introduce a number of optional pruning techniques that can significantly speed up the goal test. We discuss these pruning techniques and provide supporting experimental results.

Original languageEnglish
Title of host publicationProceedings of the 4th Annual Symposium on Combinatorial Search, SoCS 2011
Pages150-157
Number of pages8
StatePublished - 1 Dec 2011
Event4th International Symposium on Combinatorial Search, SoCS 2011 - Barcelona, Spain
Duration: 15 Jul 201116 Jul 2011

Publication series

NameProceedings of the 4th Annual Symposium on Combinatorial Search, SoCS 2011

Conference

Conference4th International Symposium on Combinatorial Search, SoCS 2011
Country/TerritorySpain
CityBarcelona
Period15/07/1116/07/11

Fingerprint

Dive into the research topics of 'Pruning techniques for the increasing cost tree search for optimal multi-agent path finding'. Together they form a unique fingerprint.

Cite this