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Level generation using genetic algorithms and difficulty testing using reinforcement learning in match-3 game
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10423950.pdf
Date
2021-9
Author
Dukkancı, Samet Alp
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The gaming industry is an enormous one that includes game development, art, and marketing. It has grown faster in recent years, especially in the mobile gaming area. Competition in mobile gaming increased in such a way that it brings us some challenges like quick prototyping, automation, minimum viable products, and so on. Level generation is the most important issue in the development period because unique and well-adjusted difficulty for a level is generally tested by humans many times for one level to assure that the level is ready to be added and it is a time consuming process. This thesis aims to come through those issues by the proposed automated level generation for a match-3 game using genetic algorithms and testing all generated levels using reinforcement algorithms to minimize the time consumption for a level designer. This helps game developers easily and quickly generate as many levels as needed.
Subject Keywords
reinforcement learning
,
genetic algorithms
,
level design
,
match-3 games
URI
https://hdl.handle.net/11511/93205
Collections
Graduate School of Natural and Applied Sciences, Thesis
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S. A. Dukkancı, “Level generation using genetic algorithms and difficulty testing using reinforcement learning in match-3 game,” M.S. - Master of Science, Middle East Technical University, 2021.