Robust Multi-Agent Path Finding and Executing
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F20%3A10424777" target="_blank" >RIV/00216208:11320/20:10424777 - isvavai.cz</a>
Výsledek na webu
<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=hDayVfHGLj" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=hDayVfHGLj</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1613/jair.1.11734" target="_blank" >10.1613/jair.1.11734</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Robust Multi-Agent Path Finding and Executing
Popis výsledku v původním jazyce
Multi-agent path-finding (MAPF) is the problem of finding a plan for moving a set of agents from their initial locations to their goals without collisions. Following this plan, however, may not be possible due to unexpected events that delay some of the agents. In this work, we propose a holistic solution for MAPF that is robust to such unexpected delays. First, we introduce the notion of a k-robust MAPF plan, which is a plan that can be executed even if a limited number (k) of delays occur. We propose sufficient and required conditions for finding a k-robust plan, and show how to convert several MAPF solvers to find such plans. Then, we propose several robust execution policies. An execution policy is a policy for agents executing a MAPF plan. An execution policy is robust if following it guarantees that the agents reach their goals even if they encounter unexpected delays. Several classes of such robust execution policies are proposed and evaluated experimentally. Finally, we present robust execution policies for cases where communication between the agents may also be delayed. We performed an extensive experimental evaluation in which we compared different algorithms for finding robust MAPF plans, compared different robust execution policies, and studied the interplay between having a robust plan and the performance when using a robust execution policy.
Název v anglickém jazyce
Robust Multi-Agent Path Finding and Executing
Popis výsledku anglicky
Multi-agent path-finding (MAPF) is the problem of finding a plan for moving a set of agents from their initial locations to their goals without collisions. Following this plan, however, may not be possible due to unexpected events that delay some of the agents. In this work, we propose a holistic solution for MAPF that is robust to such unexpected delays. First, we introduce the notion of a k-robust MAPF plan, which is a plan that can be executed even if a limited number (k) of delays occur. We propose sufficient and required conditions for finding a k-robust plan, and show how to convert several MAPF solvers to find such plans. Then, we propose several robust execution policies. An execution policy is a policy for agents executing a MAPF plan. An execution policy is robust if following it guarantees that the agents reach their goals even if they encounter unexpected delays. Several classes of such robust execution policies are proposed and evaluated experimentally. Finally, we present robust execution policies for cases where communication between the agents may also be delayed. We performed an extensive experimental evaluation in which we compared different algorithms for finding robust MAPF plans, compared different robust execution policies, and studied the interplay between having a robust plan and the performance when using a robust execution policy.
Klasifikace
Druh
J<sub>imp</sub> - 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)
Návaznosti výsledku
Projekt
<a href="/cs/project/GA19-02183S" target="_blank" >GA19-02183S: Chytré roje: od teorie k praxi</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2020
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Journal of Artificial Intelligence Research
ISSN
1076-9757
e-ISSN
—
Svazek periodika
67
Číslo periodika v rámci svazku
březen
Stát vydavatele periodika
US - Spojené státy americké
Počet stran výsledku
31
Strana od-do
549-579
Kód UT WoS článku
000528198400016
EID výsledku v databázi Scopus
2-s2.0-85090556103