prikaz prve stranice dokumenta Ocjena učinkovitosti algoritama strojnog učenja unutar simulacijskog okruženja TORCS
No public access
master's thesis
Ocjena učinkovitosti algoritama strojnog učenja unutar simulacijskog okruženja TORCS
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. urn:nbn:hr:168:579098
Torbarina, Bruno
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Torbarina, B. (2023). Ocjena učinkovitosti algoritama strojnog učenja unutar simulacijskog okruženja TORCS (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:579098

Torbarina, Bruno. "Ocjena učinkovitosti algoritama strojnog učenja unutar simulacijskog okruženja TORCS." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:579098

Torbarina, Bruno. "Ocjena učinkovitosti algoritama strojnog učenja unutar simulacijskog okruženja TORCS." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:579098

Torbarina, B. (2023). 'Ocjena učinkovitosti algoritama strojnog učenja unutar simulacijskog okruženja TORCS', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 12 May 2024, https://urn.nsk.hr/urn:nbn:hr:168:579098

Torbarina B. Ocjena učinkovitosti algoritama strojnog učenja unutar simulacijskog okruženja TORCS [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2023 [cited 2024 May 12] Available at: https://urn.nsk.hr/urn:nbn:hr:168:579098

B. Torbarina, "Ocjena učinkovitosti algoritama strojnog učenja unutar simulacijskog okruženja TORCS", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:168:579098

Metadata
TitleOcjena učinkovitosti algoritama strojnog učenja unutar simulacijskog okruženja TORCS
Title (english)Performance evaluation of machine learning algorithms in TORCS simulation environment
AuthorBruno Torbarina
MentorDomagoj Jakobović (mentor)
Committee memberDomagoj Jakobović (predsjednik povjerenstva)
Committee memberMarko Đurasević (član povjerenstva)
Committee memberLeonardo Jelenković (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2023-07-07, Croatia
Abstract
U zaključku ovog rada, upoznali smo se sa simulacijskim okruženjem TORCS, istražili različite pristupe strojnom učenju i njihovu primjenu u autonomnoj vožnji. Posebno smo se usredotočili na genetski algoritam i DDPG (Deep Deterministic Policy Gradient) algoritam. Detaljno smo opisali njihovu programsku implementaciju i korištene tehnologije u svrhu ostvarenja ovog rada. Na kraju, iznijeli smo rezultate genetskog algoritma i DDPG algoritma, te smo ih usporedili i procijenili njihovu korisnost za rješavanje ovog problema.
Abstract (english)
In conclusion of this study, we familiarized ourselves with the TORCS simulation environment and explored various machine learning approaches and their application in autonomous driving. We specifically focused on the genetic algorithm and DDPG (Deep Deterministic Policy Gradient) algorithm. We provided detailed insights into their programming implementation and the technologies used to accomplish the objectives of this work. Finally, we presented the results of the genetic algorithm and DDPG algorithm, comparing and evaluating their utility for solving this problem.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:579098
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
Terms of useLicence In copyright icon
Public note
Created on2023-10-11 10:48:49