Analytic hierarchy process 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%2F18%3A50005427" target="_blank" >RIV/62690094:18450/18:50005427 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.3233/AIS-180480" target="_blank" >http://dx.doi.org/10.3233/AIS-180480</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3233/AIS-180480" target="_blank" >10.3233/AIS-180480</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Analytic hierarchy process in artificial life model based on fuzzy cognitive maps

Popis výsledku v původním jazyce

The paper describes a new approach to the modeling of individual-based artificial life models based on fuzzy cognitive maps (FCMs). The proposed concept focuses on the optimization of the artificial intelligence of individuals in multi-agent models and their adaptation to an environment. The emphasis is put on the decision-making method. FCMs offer great complexity and may be extended for learning through evolutionary algorithms. However, large FCMs suffer from high computational performance issues. This paper presents the possibility of replacing the decision-making part of an FCM with the analytic hierarchy process (AHP) method, which is widely used for decision support. Some sections in FCMs are often unused or insignificant for individuals’ behavior. Since AHP needs fewer inputs to make decisions on the same set of possible actions, this approach offers lower demands but also fewer possibilities for the development of behavior. This paper describes a transformation of an FCM into a combination of both these methods (FCM-AHP) and tests strengths and weaknesses of the approaches in the artificial life model. In comparison to the larger FCM, FCM-AHP provides a model with significantly lower computational demands while keeping nearly the same complexity.

Název v anglickém jazyce

Analytic hierarchy process in artificial life model based on fuzzy cognitive maps

Popis výsledku anglicky

The paper describes a new approach to the modeling of individual-based artificial life models based on fuzzy cognitive maps (FCMs). The proposed concept focuses on the optimization of the artificial intelligence of individuals in multi-agent models and their adaptation to an environment. The emphasis is put on the decision-making method. FCMs offer great complexity and may be extended for learning through evolutionary algorithms. However, large FCMs suffer from high computational performance issues. This paper presents the possibility of replacing the decision-making part of an FCM with the analytic hierarchy process (AHP) method, which is widely used for decision support. Some sections in FCMs are often unused or insignificant for individuals’ behavior. Since AHP needs fewer inputs to make decisions on the same set of possible actions, this approach offers lower demands but also fewer possibilities for the development of behavior. This paper describes a transformation of an FCM into a combination of both these methods (FCM-AHP) and tests strengths and weaknesses of the approaches in the artificial life model. In comparison to the larger FCM, FCM-AHP provides a model with significantly lower computational demands while keeping nearly the same complexity.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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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

2018

Kód důvěrnosti údajů

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

Název periodika

Journal of ambient intelligence and smart environments

ISSN

1876-1364

e-ISSN

—

Svazek periodika

10

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

15

Strana od-do

127-141

Kód UT WoS článku

000428368600003

EID výsledku v databázi Scopus

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