Artificial intelligence based on MCDM for the board game of the Royal Game of Ur
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12510%2F23%3A43906549" target="_blank" >RIV/60076658:12510/23:43906549 - isvavai.cz</a>
Result on the web
<a href="https://www.inderscience.com/info/inarticle.php?artid=133145" target="_blank" >https://www.inderscience.com/info/inarticle.php?artid=133145</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1504/IJADS.2023.133138" target="_blank" >10.1504/IJADS.2023.133138</a>
Alternative languages
Result language
angličtina
Original language name
Artificial intelligence based on MCDM for the board game of the Royal Game of Ur
Original language description
The Royal Game of Ur is an ancient board game with random elements and strategies. We introduce two methods of designing simple but effective artificial intelligence (AI) that performs well in this game against both human players and the chosen AI available online. The multiple-criteria decision-making methods in use are the lexicographic semi-order method and the weighted sum method.
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
10102 - Applied mathematics
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
International Journal of Applied Decision Sciences
ISSN
1755-8077
e-ISSN
1755-8085
Volume of the periodical
16
Issue of the periodical within the volume
5
Country of publishing house
CH - SWITZERLAND
Number of pages
10
Pages from-to
545-564
UT code for WoS article
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EID of the result in the Scopus database
2-s2.0-85171612906