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Learning Blackjack using reinforcement learning

Žiga Franko Gorišek (2018) Learning Blackjack using reinforcement learning. EngD thesis.

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    Through the study process, I gained a lot of knowledge and interests in fields such as algorithms, optimization, betting, finance and artificial intelligence. So I developed a desire to specialize in Deep Learning. I wanted to achieve a level of knowledge and understanding of how to use the learned specialization with the latest machine learning technologies. I was also extremely impressed by the story about MIT students who discovered and used the Black jack hole from which they opened a profitable game. So I decided to make a system that learns how to discover the legitimacy of the Black jack game, to learn DQN techniques and try to improve the basis of their system with it.

    Item Type: Thesis (EngD thesis)
    Keywords: DQN, Neural network, Black jack, dealer, player, model
    Number of Pages: 55
    Language of Content: Slovenian
    Mentor / Comentors:
    Name and SurnameIDFunction
    doc. dr. Aleksander Sadikov934Mentor
    Link to COBISS: http://www.cobiss.si/scripts/cobiss?command=search&base=51012&select=(ID=1537883843)
    Institution: University of Ljubljana
    Department: Faculty of Computer and Information Science
    Item ID: 4157
    Date Deposited: 28 Aug 2018 16:15
    Last Modified: 07 Sep 2018 11:24
    URI: http://eprints.fri.uni-lj.si/id/eprint/4157

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