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Title:Uporaba okrepitvenega učenja za optimizacijo krmiljenja semaforjev : diplomsko delo
Authors:ID Sušin, Žiga (Author)
ID Podgorelec, Vili (Mentor) More about this mentor... New window
Files:.pdf UN_Susin_Ziga_2021.pdf (1,21 MB)
MD5: D40E7DC7D42F6A0B97539EA6E27B2637
PID: 20.500.12556/dkum/f9f4f817-2749-4ed1-8c54-211ad1a6402a
 
Language:Slovenian
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V tej nalogi bomo podrobno preučili metodo okrepitvenega učenja in načine implementacije le-tega. Nato ga bomo uporabili za rešitev zadanega problema, ki je optimizacija krmiljenja semaforjev v križišču. V naslednjih poglavjih bomo na splošno opisali strojno učenje, podrobneje pa okrepitveno učenje. Opisali bomo tudi način implementacije v programskem jeziku Python in knjižnice, ki nam pomagajo pri tem. V drugem delu naloge bomo izdelali program s pomočjo pridobljenega znanja. Na koncu pa bomo še predstavili rezultate simulacij.
Keywords:Okrepitveno učenje, umetna inteligenca, promet, Python
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[Ž. Sušin]
Year of publishing:2021
Number of pages:VIII, 38 str.
PID:20.500.12556/DKUM-80391 New window
UDC:004.85.021:004.43(043.2)
COBISS.SI-ID:89434371 New window
Publication date in DKUM:18.10.2021
Views:1387
Downloads:78
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:10.09.2021

Secondary language

Language:English
Title:Reinforcement learning for traffic light control optimization
Abstract:In this paper we will study the method of reinforcement learning and the ways of its implementation. We will then use the knowledge gained, to solve the given problem, which is optimization of traffic light controls. In chapters that follow, we will describe machine learning in general, and than we will focus more on reinforcement learning and describe it in detail. We will then describe how to implement it in Python programing language and the libraries that help us with its implementation. In the second part of this paper, we will create a program with the acquired knowledge. In the end, we will present the results of the simulation.
Keywords:Reinforcement learning, artificial intelligence, traffic, Python


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