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http://dspace.lib.uom.gr/handle/2159/25182
Author: | Καμανάς, Παντελής-Αρσένιος |
Title: | Design and analysis of slot machine games and RTP optimization using variable neighborhood search (VNS) |
Date Issued: | 2021 |
Department: | Πρόγραμμα Μεταπτυχιακών Σπουδών Ειδίκευσης στην Εφαρμοσμένη Πληροφορική |
Supervisor: | Σιφαλέρας, Άγγελος |
Abstract: | Slot machines, also known as fruit machines, are the most popular gambling games in casinos. They are either electronic or electro-mechanical devices that consist of a number of reels that spin independently and a screen with a number of rows. Each reel contains several symbols in specific arrangements and quantities. This work presents the process of design and analysis of complex slot machine games. Additionally, a Variable Neighborhood Search (VNS) approach is presented for solving the Return-To-Player (RTP) optimization problem. A large number of software companies in the gaming industry seeks to solve the RTP optimization problem, in order to develop modern virtual casino gambling machines. By using a VNS framework which guides two local search operators we show how to control the distribution of the symbols in the reels in order to achieve the desired RTP. In this manuscript, optimization refers only to base game, the core of slot machine games, and not in bonus games, since a bonus game is triggered once two, three or more specific symbols occur in the gaming monitor. Although, other researchers have tried to solve the RTP problem in the past, this is the first time that a VNS methodology is proposed for this problem in the literature with good computational results. |
Keywords: | Variable Neighborhood Search Metaheuristics VND Game Design RTP Optimization Slot Machine Gambling Design |
Information: | Διπλωματική εργασία--Πανεπιστήμιο Μακεδονίας, Θεσσαλονίκη, 2021. |
Rights: | Αναφορά Δημιουργού 4.0 Διεθνές |
Appears in Collections: | Π.Μ.Σ. στην Εφαρμοσμένη Πληροφορική (M) |
Files in This Item:
File | Description | Size | Format | |
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KamanasPantelisArseniosMsc2021.pdf | 9.51 MB | Adobe PDF | View/Open | |
KamanasPantelisArseniosMsc2021present.pdf | Παρουσίαση | 677.67 kB | Adobe PDF | View/Open |
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