Multiple Data Cubes and the Best Compromise Matrix for the OLAP in Multi-agent System

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Multiple Data Cubes and the Best Compromise Matrix for the OLAP in Multi-agent System

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Multiple Data Cubes and the Best Compromise Matrix for the OLAP in Multi-agent System

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

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

Počet stran výsledku

10

Strana od-do

980-989

Název nakladatele

Springer

Místo vydání

Cham

Místo konání akce

Online

Datum konání akce

1. 1. 2022

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000992418500084