Multi-agent path finding with mutex propagation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F22%3A00360668" target="_blank" >RIV/68407700:21240/22:00360668 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1016/j.artint.2022.103766" target="_blank" >https://doi.org/10.1016/j.artint.2022.103766</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.artint.2022.103766" target="_blank" >10.1016/j.artint.2022.103766</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Multi-agent path finding with mutex propagation

Popis výsledku v původním jazyce

Mutex propagation is a form of efficient constraint propagation popularly used in AI planning to tightly approximate the reachable states from a given state. We utilize this idea in the context of Multi-Agent Path Finding (MAPF). When adapted to MAPF, mutex propagation provides stronger constraints for conflict resolution in CBS, a popular optimal search-based MAPF algorithm, as well as in MDD-SAT, an optimal satisfiability-based MAPF algorithm. Mutex propagation provides CBS with the ability to break symmetries in MAPF and provides MDD-SAT with the ability to make stronger inferences than unit propagation. While existing work identifies a limited form of symmetries and requires the manual design of symmetry-breaking constraints, mutex propagation is more general and allows for the automated design of symmetry-breaking constraints. Our experimental results show that CBS with mutex propagation is capable of outperforming CBSH-RCT, a state-of-the-art variant of CBS, with respect to the success rate. We also show that MDD-SAT with mutex propagation often performs better than MDD-SAT with respect to the success rate.

Název v anglickém jazyce

Multi-agent path finding with mutex propagation

Popis výsledku anglicky

Mutex propagation is a form of efficient constraint propagation popularly used in AI planning to tightly approximate the reachable states from a given state. We utilize this idea in the context of Multi-Agent Path Finding (MAPF). When adapted to MAPF, mutex propagation provides stronger constraints for conflict resolution in CBS, a popular optimal search-based MAPF algorithm, as well as in MDD-SAT, an optimal satisfiability-based MAPF algorithm. Mutex propagation provides CBS with the ability to break symmetries in MAPF and provides MDD-SAT with the ability to make stronger inferences than unit propagation. While existing work identifies a limited form of symmetries and requires the manual design of symmetry-breaking constraints, mutex propagation is more general and allows for the automated design of symmetry-breaking constraints. Our experimental results show that CBS with mutex propagation is capable of outperforming CBSH-RCT, a state-of-the-art variant of CBS, with respect to the success rate. We also show that MDD-SAT with mutex propagation often performs better than MDD-SAT with respect to the success rate.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/GA22-31346S" target="_blank" >GA22-31346S: logicMOVE: Logické uvažování v plánování pohybu pro mnoho robotických agentů</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Artificial Intelligence

ISSN

0004-3702

e-ISSN

1872-7921

Svazek periodika

2022

Číslo periodika v rámci svazku

311

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

21

Strana od-do

—

Kód UT WoS článku

000843869600001

EID výsledku v databázi Scopus

2-s2.0-85135327187