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Title:OPTIMIZACIJA PARAMETROV SIMULIRANEGA SOCIALNO-EKONOMSKEGA SISTEMA Z GENETSKIM ALGORITMOM
Authors:ID Borko, Aljaž (Author)
ID Strnad, Damjan (Mentor) More about this mentor... New window
Files:.pdf UNI_Borko_Aljaz_2014.pdf (1,66 MB)
MD5: 872FEE0FFE2D854AB6FE9486B580CB17
 
Language:Slovenian
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V diplomskem delu je predstavljen genetski algoritem in njegova implementacija za optimiziranje parametrov v simuliranem socialno-ekonomskem sistemu, v katerem nastopajo entitete, kot so agenti, drevesa, hrana itd. Vsak tip entitete ima svoje lastnosti in omejitve. Delovanje sistema je predpisano z implicitnimi pravili, ki določajo medsebojne vplive entitet. Parametri, ki jih optimiziramo, vplivajo na obnašanje agentov, ki so glavni skrbniki sistema. S tem želimo vzpostaviti stabilen sistem, ki bi preživel čim dlje. V diplomskem delu pokažemo, da lahko ta cilj dosežemo s pomočjo genetskega algoritma, ki poišče optimalne vrednosti omenjenih parametrov.
Keywords:Genetski algoritem, evolucijski algoritmi, simulacija, optimizacija parametrov
Place of publishing:Maribor
Publisher:[A. Borko]
Year of publishing:2014
PID:20.500.12556/DKUM-45356 New window
UDC:004.986(043.2)
COBISS.SI-ID:18287126 New window
NUK URN:URN:SI:UM:DK:X4XPSZN8
Publication date in DKUM:19.11.2014
Views:1881
Downloads:120
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
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Secondary language

Language:English
Title:OPTIMIZATION OF PARAMETERS OF SIMULATED SOCIAL-ECONOMIC SYSTEM WITH GENETIC ALGORITHM
Abstract:This diploma paper discusses genetic algorithm and its implementation in order to optimize parameters in a simulated socio-economic system, including entities such as agents, trees, food, etc. Each type of entity has its own characteristics and limitations. Activity of the system is in accordance to rules and regulations of implicit standards that determine interacting influences of entities. When parameters are optimised, they influence the behaviour of agents that are the systems main administrators. Thus, this enables us to establish a stable system with the longest survival time possible. As shown in this paper, this can be achieved by using genetic algorithm that establishes optimal values of mentioned parameters.
Keywords:Genetic algorithm, evolution algorithm, simulation, parameter optimization


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