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master's thesis
Samoadaptivno mrežno usmjeravanje
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. urn:nbn:hr:168:764097
Čupković, Robert
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Čupković, R. (2019). Samoadaptivno mrežno usmjeravanje (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:764097

Čupković, Robert. "Samoadaptivno mrežno usmjeravanje." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. https://urn.nsk.hr/urn:nbn:hr:168:764097

Čupković, Robert. "Samoadaptivno mrežno usmjeravanje." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. https://urn.nsk.hr/urn:nbn:hr:168:764097

Čupković, R. (2019). 'Samoadaptivno mrežno usmjeravanje', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 25 June 2024, https://urn.nsk.hr/urn:nbn:hr:168:764097

Čupković R. Samoadaptivno mrežno usmjeravanje [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2019 [cited 2024 June 25] Available at: https://urn.nsk.hr/urn:nbn:hr:168:764097

R. Čupković, "Samoadaptivno mrežno usmjeravanje", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2019. Available at: https://urn.nsk.hr/urn:nbn:hr:168:764097

Metadata
TitleSamoadaptivno mrežno usmjeravanje
Title (english)Selfadaptive network routing
AuthorRobert Čupković
MentorDragan Jevtić (mentor)
Committee memberDragan Jevtić (predsjednik povjerenstva)
Committee memberMarin Vuković (član povjerenstva)
Committee memberMiljenko Mikuc (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2019-07-05, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Problem usmjeravanja informacija zahtjeva inteligentno rješenje uslijed konstantnih promjena u telekomunikacijskoj mreži. Jedna od mogućnosti je primjena algoritma iz područja poticanog učenja, podvrste strojnog učenja u kojoj softverski agent na temelju pokušaja i pogrešaka upoznaje svoju okolinu koja ga poticajima usmjerava prema cilju. Često korišteni algoritam poticanog učenja je Q-učenje. Za pohranu Q vrijednosti koristi se Q tablica, no nju se može zamijeniti umjetnom neuronskom mrežom ako je prihvatljivo izgubiti dio preciznosti. U području mrežnog usmjeravanja Q-algoritmom, neka od rješenja su Q-usmjeravanje, Full-Echo Q-usmjeravanje i Dual Reinforcement Q-usmjeravanje. Pri implementaciji laboratorijskog modela spojeno je Full-Echo Q-usmjeravanje s dubokim Q-učenjem te je napravljena validacija istog. Dobiveni su zadovoljavajući rezultati i pokazalo se da odabrani pristup ima prostora za napredak u budućnosti.
Abstract (english)
The problem of routing information requires an intelligent solution due to constant changes in a telecommunications network. One possibility is applying an algorithm from the field of reinforcement learning, an area of machine learning in which a software agent learns about his environment using the method of trial and error, all the while the environment guides him towards the goal. Q-learning is an example of an often used reinforcement learning algorithm. A table is used in order to store Q values, however it can be replaced with an artificial neural network if it's acceptable to lose some accuracy. In the field of network routing, some Q-algorithm-based solutions include Q-routing, Full-Echo Q-routing and Dual Reinforcement Q-routing. The implementation of the laboratory model combines Full-Echo Q-routing with Deep Q-learning and includes the validation of said model. The ending results are satisfactory and it's shown there's room for improvement in the future using the described approach.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:764097
Study programmeTitle: Computing
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2020-01-07 17:27:11