At-Most-One Constraints in Efficient Representations of Mutex Networks
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F20%3A00345316" target="_blank" >RIV/68407700:21240/20:00345316 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/ICTAI50040.2020.00036" target="_blank" >https://doi.org/10.1109/ICTAI50040.2020.00036</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICTAI50040.2020.00036" target="_blank" >10.1109/ICTAI50040.2020.00036</a>
Alternative languages
Result language
angličtina
Original language name
At-Most-One Constraints in Efficient Representations of Mutex Networks
Original language description
he At-Most-One (AMO) constraint is a special case of cardinality constraint that requires at most one variable from a set of Boolean variables to be set to TRUE . AMO is important for modeling problems as Boolean satisfiability (SAT) from domains where decision variables represent spatial or temporal placements of some objects that cannot share the same spatial or temporal slot. The AMO constraint can be used for more efficient representation and problem solving in mutex networks consisting of pair-wise mutual exclusions forbidding pairs of Boolean variable to be simultaneously TRUE.
Czech name
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Czech description
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Classification
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)
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
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 32nd IEEE International Conference on Tools with Artificial Intelligence
ISBN
978-1-7281-9228-4
ISSN
2375-0197
e-ISSN
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Number of pages
8
Pages from-to
170-177
Publisher name
IEEE Computer Society
Place of publication
Los Alamitos
Event location
Virtualni
Event date
Nov 9, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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