Multiple Data Cubes and the Best Compromise Matrix for the OLAP in Multi-agent System
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41110%2F23%3A92870" target="_blank" >RIV/60460709:41110/23:92870 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-031-21438-7_84" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-031-21438-7_84</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-21438-7_84" target="_blank" >10.1007/978-3-031-21438-7_84</a>
Alternative languages
Result language
angličtina
Original language name
Multiple Data Cubes and the Best Compromise Matrix for the OLAP in Multi-agent System
Original language description
Multi-agent systems are systems that can perceive the environment through their sensors and perform actions through their actuators. Multi-agent systems are thus an interesting alternative or complement to artificial intelligence. One of the key problems of these systems is designing the principles of agent behavior through coordination, cooperation, and communication, which bring order to the actions of agents and ensure that there are no contradictions in the system. The development of OLAP technology to support online analytical data processing enables the use multidimensional data stores directly by individual agents. In this way, the agent can streamline the analytical processing of the data to find a match between its intention and the plan. For the resulting multi-agent system to find the maximum possible agreement between its agents, we propose a new conceptual approach, which is based on the use of OLAP technology for storing analytical data by specific agents, and we propose the so-called Compromise Decision Agent, which calculates compromise values from all agents in the system.
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
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2023
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 Computational Methods in Systems and Software, CoMeSySo 2022: Data Science and Algorithms in Systems. Lecture Notes in Networks and Systems, vol 597.
ISBN
978-3-031-21438-7
ISSN
2367-3370
e-ISSN
2367-3389
Number of pages
10
Pages from-to
980-989
Publisher name
Springer
Place of publication
Cham
Event location
Online
Event date
Jan 1, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000992418500084