Multi-agent path finding with mutex propagation
The result's identifiers
Result code in 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>
Result on the web
<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>
Alternative languages
Result language
angličtina
Original language name
Multi-agent path finding with mutex propagation
Original language description
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.
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/GA22-31346S" target="_blank" >GA22-31346S: logicMOVE: Logic Reasoning in Motion Planning for Multiple Robotic Agents</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
Artificial Intelligence
ISSN
0004-3702
e-ISSN
1872-7921
Volume of the periodical
2022
Issue of the periodical within the volume
311
Country of publishing house
GB - UNITED KINGDOM
Number of pages
21
Pages from-to
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UT code for WoS article
000843869600001
EID of the result in the Scopus database
2-s2.0-85135327187