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master's thesis
Primjena metoda podržanog učenja u domeni autonomnog parkiranja
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. urn:nbn:hr:168:480417
Marfat, Marko
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Marfat, M. (2023). Primjena metoda podržanog učenja u domeni autonomnog parkiranja (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:480417

Marfat, Marko. "Primjena metoda podržanog učenja u domeni autonomnog parkiranja." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:480417

Marfat, Marko. "Primjena metoda podržanog učenja u domeni autonomnog parkiranja." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:480417

Marfat, M. (2023). 'Primjena metoda podržanog učenja u domeni autonomnog parkiranja', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 20 January 2025, https://urn.nsk.hr/urn:nbn:hr:168:480417

Marfat M. Primjena metoda podržanog učenja u domeni autonomnog parkiranja [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2023 [cited 2025 January 20] Available at: https://urn.nsk.hr/urn:nbn:hr:168:480417

M. Marfat, "Primjena metoda podržanog učenja u domeni autonomnog parkiranja", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:168:480417

Metadata
TitlePrimjena metoda podržanog učenja u domeni autonomnog parkiranja
Title (english)Leveraging Reinforced Learning Methods in the Domain of Autonomous Parking
AuthorMarko Marfat
MentorDamir Pintar (mentor)
Committee memberDamir Pintar (predsjednik povjerenstva)
Committee memberMihaela Vranić (član povjerenstva)
Committee memberLuka Humski (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2023-07-13, Croatia
Abstract
Podržano učenje je dio strojnog učenja koji se bavi učenjem modela umjetne inteligencije kako bi bio računalni sustav bio sposoban autonomno donositi odluke ovisno o parametrima svojeg okruženja. Model s vremenom nauči maksimizirati nagradu koju dobije kada donese ispravnu odluku. Zadatak diplomskog rada je razviti model za autonomno parkiranje koristeći metode podržanog učenja. U radu će se uz pomoć metoda podržanog učenja oblikovati programska simulacija čija je svrha omogućiti računalu automatsko učenje upravljanja modela virtualnog vozila kako bi se isto moglo parkirati na simuliranom parkingu s raznim preprekama. Rad će također istražiti i primjenu dobivenih rezultata u stvarnom svijetu koristeći manji model vozila. Cilj je pružiti uvid u potencijal podržanog učenja u domeni autonomne vožnje i u razvoj inteligentnih autonomnih sustava.
Abstract (english)
Reinforced learning is a subset of machine learning that specializes in training AI models in such a way that a computer system is able to make decisions autonomously depending on the parameters of its environment. Over time, the model learns to maximize the reward it gets when it makes the right decision. The goal of the thesis is to develop a model for autonomous parking using reinforced learning methods. In the thesis, with the help of reinforced learning methods, a software simulation will be created whose purpose is to enable the computer to automatically learn to control a virtual vehicle model with the goal of being able to park in a simulated parking lot with various obstacles. The thesis will also explore the application of the obtained results in the real world using a small model vehicle. The goal is to provide insight into the potential of reinforced learning in the domain of autonomous driving and into the development of intelligent autonomous systems.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:480417
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
Access conditionsClosed access
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Created on2023-10-11 09:39:31