Level generation using genetic algorithms and difficulty testing using reinforcement learning in match-3 game

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2021-9

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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

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Graduate School of Natural and Applied Sciences, Thesis

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Citation Formats

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.