Fuzzy cognitive maps for decision-making in dynamic environments

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F21%3A50016765" target="_blank" >RIV/62690094:18450/21:50016765 - isvavai.cz</a>

Výsledek na webu

<a href="https://rdcu.be/b4q6E" target="_blank" >https://rdcu.be/b4q6E</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s10710-020-09393-2" target="_blank" >10.1007/s10710-020-09393-2</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Fuzzy cognitive maps for decision-making in dynamic environments

Popis výsledku v původním jazyce

This paper describes a new modification of fuzzy cognitive maps (FCMs) for the modeling of autonomous entities that make decisions in a dynamic environment. The paper offers a general design for an FCM adjusted for the decision-making of autonomous agents through the categorization of its concepts into three different classes according to their purpose in the map: Needs, Activities, and States (FCM-NAS). The classification enables features supporting decision-making, such as the easy processing of input from sensors, faster system reactions, the modeling of inner needs, the adjustable frequency of computations in a simulation, and self-evaluation of the FCM-NAS that supports unsupervised evolutionary learning. This paper presents two use cases of the proposed extension to demonstrate its abilities. It was implemented into an agent-based artificial life model, where it took advantage of all the above features in the competition for resources, natural selection, and evolution. Then, it was used as decision-making for human activity simulation in an ambient intelligence model, where it is combined with scenario-oriented mechanism proving its modularity.

Název v anglickém jazyce

Fuzzy cognitive maps for decision-making in dynamic environments

Popis výsledku anglicky

This paper describes a new modification of fuzzy cognitive maps (FCMs) for the modeling of autonomous entities that make decisions in a dynamic environment. The paper offers a general design for an FCM adjusted for the decision-making of autonomous agents through the categorization of its concepts into three different classes according to their purpose in the map: Needs, Activities, and States (FCM-NAS). The classification enables features supporting decision-making, such as the easy processing of input from sensors, faster system reactions, the modeling of inner needs, the adjustable frequency of computations in a simulation, and self-evaluation of the FCM-NAS that supports unsupervised evolutionary learning. This paper presents two use cases of the proposed extension to demonstrate its abilities. It was implemented into an agent-based artificial life model, where it took advantage of all the above features in the competition for resources, natural selection, and evolution. Then, it was used as decision-making for human activity simulation in an ambient intelligence model, where it is combined with scenario-oriented mechanism proving its modularity.

Druh

J_imp - Článek v periodiku v databázi Web of Science

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

2021

Kód důvěrnosti údajů

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

Název periodika

Genetic programming and evolvable machines

ISSN

1389-2576

e-ISSN

—

Svazek periodika

22

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

35

Strana od-do

101-135

Kód UT WoS článku

000558751900001

EID výsledku v databázi Scopus

2-s2.0-85085479714