Multi-Goal Multi-Agent Path Finding via Decoupled and Integrated Goal Vertex Ordering

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F21%3A00350486" target="_blank" >RIV/68407700:21240/21:00350486 - isvavai.cz</a>

Result on the web

<a href="https://ojs.aaai.org/index.php/AAAI/article/view/17472" target="_blank" >https://ojs.aaai.org/index.php/AAAI/article/view/17472</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Multi-Goal Multi-Agent Path Finding via Decoupled and Integrated Goal Vertex Ordering

Original language description

We introduce multi-goal multi agent path finding (MG-MAPF) which generalizes the standard discrete multi-agent path finding (MAPF) problem. While the task in MAPF is to navigate agents in an undirected graph from their starting vertices to one individual goal vertex per agent, MG-MAPF assigns each agent multiple goal vertices and the task is to visit each of them at least once. Solving MG-MAPF not only requires finding collision free paths for individual agents but also determining the order of visiting agent's goal vertices so that common objectives like the sum-of-costs are optimized. We suggest two novel algorithms using different paradigms to address MG-MAPF: a heuristic search-based algorithm called Hamiltonian-CBS (HCBS) and a compilation-based algorithm built using the satisfiability modulo theories (SMT), called SMT-Hamiltonian-CBS (SMT-HCBS).

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

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

Project

<a href="/en/project/GA19-17966S" target="_blank" >GA19-17966S: intALG-MAPFg: Intelligent Algorithms for Generalized Variants of Multi-Agent Path Finding</a><br>

Continuities

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

Publication year

2021

Confidentiality

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

Article name in the collection

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence

ISBN

978-1-57735-866-4

ISSN

2159-5399

e-ISSN

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Number of pages

9

Pages from-to

12409-12417

Publisher name

AAAI Press

Place of publication

Menlo Park

Event location

Virtual

Event date

Feb 2, 2021

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000681269804010