Potencial uporabe samoojačitvenega učenja za pametni nabiralnik Direct4.me : diplomsko delo

Smolak, Eva

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Title:	Potencial uporabe samoojačitvenega učenja za pametni nabiralnik Direct4.me : diplomsko delo
Authors:	ID Smolak, Eva (Author) ID Zorman, Milan (Mentor) More about this mentor... ID Stropnik, Ambrož (Comentor)
Files:	UN_Smolak_Eva_2020.pdf (1,59 MB) MD5: D6F016E5EB30A5ABF90E607D453C3772 PID: 20.500.12556/dkum/99055a9c-0a00-4a1d-8db7-93ad2261ed29
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, izdelanem pod mentorstvom podjetja Kivi Com d.o.o., smo preučili samoojačitveno učenje, metode samoojačitvenega učenja, globoko samoojačitveno učenje in nevronske mreže. Prav tako smo na kratko opisali priljubljena ogrodja samoojačitvenega učenja in izdelali simulator sistema Direct4.me, kjer smo implementirali postopek dostavljanja in prevzemanja paketov oziroma odpiranja paketnikov. Simulator smo ustvarili v programskem jeziku C#, za izdelavo, učenje in uporabo nevronske mreže pa smo uporabili Python in knjižnico Scikit-learn. Na podlagi simulatorja in nevronske mreže smo preučili potencial uporabe samoojačitvenega učenja v sistemu Direct4.me.
Keywords:	samoojačitveno učenje, Direct4.me, umetna inteligenca
Place of publishing:	Maribor
Place of performance:	Maribor
Publisher:	[E. Smolak]
Year of publishing:	2020
Number of pages:	IX, 45 f.
PID:	20.500.12556/DKUM-76940
UDC:	004.85(043.2)
COBISS.SI-ID:	39239683
NUK URN:	URN:SI:UM:DK:N2XOOCTU
Publication date in DKUM:	04.11.2020
Views:	1158
Downloads:	120
Metadata:
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:	01.08.2020

Secondary language

Language:	English
Title:	The potential of reinforcement learning in the Direct4.me smart box application
Abstract:	In this thesis, prepared under the mentorship of Kivi Com d.o.o., we examined reinforcement learning, methods of reinforcement learning, deep reinforcement learning and neural networks. We also shortly described most used reinforcement learning frameworks and created a simulator of the Direct4.me system, where we implemented the procedure of delivering and receiving packages or opening smart boxes. We wrote the simulator in the C# programming language and used Python with Scikit-learn library to build, train, and use the neural network. By combining a simulator and a neural network, we examined the potential of using reinforcement learning in the Direct4.me smart box application.
Keywords:	reinforcement learning, Direct4.me, artificial intelligence

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