Migrating Techniques from Search-based Multi-Agent Path Finding Solvers to SAT-based Approach
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F22%3A00357052" target="_blank" >RIV/68407700:21240/22:00357052 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1613/jair.1.13318" target="_blank" >https://doi.org/10.1613/jair.1.13318</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1613/jair.1.13318" target="_blank" >10.1613/jair.1.13318</a>
Alternative languages
Result language
angličtina
Original language name
Migrating Techniques from Search-based Multi-Agent Path Finding Solvers to SAT-based Approach
Original language description
In the multi-agent path finding problem (MAPF) we are given a set of agents each with re- spective start and goal positions. The task is to find paths for all agents while avoiding collisions, aiming to minimize a given objective function. Many MAPF solvers were introduced in the past decade for optimizing two specific objective functions: sum-of-costs and makespan. Two prominent categories of solvers can be distinguished: search-based solvers and compilation-based solvers. Search-based solvers were developed and tested for the sum-of-costs objective, while the most prominent compilation-based solvers that are built around Boolean satisfiability (SAT) were designed for the makespan objective. Very little is known on the performance and relevance of solvers from the compilation-based approach on the sum-of-costs objective. In this paper, we start to close the gap between these cost functions in the compilation-based approach.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
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)
Result continuities
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)
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Journal of Artificial Intelligence Research
ISSN
1076-9757
e-ISSN
1943-5037
Volume of the periodical
2022
Issue of the periodical within the volume
73
Country of publishing house
US - UNITED STATES
Number of pages
66
Pages from-to
553-618
UT code for WoS article
000755563700002
EID of the result in the Scopus database
2-s2.0-85125937283