Optimization of Decision-Making in Artificial Life Model Based on Fuzzy Cognitive Maps

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F15%3A50003677" target="_blank" >RIV/62690094:18450/15:50003677 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/IE.2015.28" target="_blank" >http://dx.doi.org/10.1109/IE.2015.28</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/IE.2015.28" target="_blank" >10.1109/IE.2015.28</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Optimization of Decision-Making in Artificial Life Model Based on Fuzzy Cognitive Maps

Popis výsledku v původním jazyce

The paper describes a new approach to the modeling of the individual-based artificial life model based on fuzzy cognitive maps (FCM). The proposed concept focuses on the optimization of artificial intelligence of individuals in multi-agent models and their adaptation to environment. In this process of optimization, emphasis is put on the decision-making method. FCM offers great complexity and learning through evolutionary algorithms. However, too large FCMs suffer from performance issues. Therefore, this paper presents a possibility to replace a decision-making part of large FCM with the analytic hierarchy process (AHP) method, which is widely used, Eespecially for decision support. In comparison with the large FCM model, a combination with AHP provides a model with lower computational demands while keeping nearly the same complexity.

Název v anglickém jazyce

Optimization of Decision-Making in Artificial Life Model Based on Fuzzy Cognitive Maps

Popis výsledku anglicky

The paper describes a new approach to the modeling of the individual-based artificial life model based on fuzzy cognitive maps (FCM). The proposed concept focuses on the optimization of artificial intelligence of individuals in multi-agent models and their adaptation to environment. In this process of optimization, emphasis is put on the decision-making method. FCM offers great complexity and learning through evolutionary algorithms. However, too large FCMs suffer from performance issues. Therefore, this paper presents a possibility to replace a decision-making part of large FCM with the analytic hierarchy process (AHP) method, which is widely used, Eespecially for decision support. In comparison with the large FCM model, a combination with AHP provides a model with lower computational demands while keeping nearly the same complexity.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název statě ve sborníku

Intelligent environments (IE 2015)

ISBN

978-1-4673-6654-0

ISSN

—

e-ISSN

—

Počet stran výsledku

4

Strana od-do

136-139

Název nakladatele

IEEE

Místo vydání

Piscataway

Místo konání akce

Prague

Datum konání akce

15. 7. 2015

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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