Maze generation based on difficulty using genetic algorithm with gene pool

Evan Kusuma Susanto, Rifqi Fachruddin, Muhammad Ihsan Diputra, Darlis Herumurti, Andhik Ampuh Yunanto

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)

Abstract

Game level design is one of the most important element of developing an enjoyable video game. Besides, game with difficult and dynamic level can make players more exciting. This paper presents a new method of generating a video game level using a genetic algorithm. The proposed method is called gene pool integrates learning. This method implemented in feature selection so that this method is general enough to be used for multiple different types of games. This paper uses some training data to scan good patterns and store all of them in a gene pool. Furthermore, the genetic algorithm is used to find the combination of patterns that can produce the best result. The gene pool also records the quality of each gene so it can learn the pattern which most commonly found in multiple levels. For testing, this research develops a custom game with complicated rules that are hard to represent by a simple 2D array compared to the previously attempted work. The result of this research shows that the method can generate many complicated levels at once. Overall, levels generated using this method on average requires almost 3 times more steps to solve than the dataset.

Original languageEnglish
Title of host publicationProceedings - 2020 International Seminar on Application for Technology of Information and Communication
Subtitle of host publicationIT Challenges for Sustainability, Scalability, and Security in the Age of Digital Disruption, iSemantic 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages554-559
Number of pages6
ISBN (Electronic)9781728190686
DOIs
Publication statusPublished - 19 Sept 2020
Event2020 International Seminar on Application for Technology of Information and Communication, iSemantic 2020 - Semarang, Indonesia
Duration: 19 Sept 202020 Sept 2020

Publication series

NameProceedings - 2020 International Seminar on Application for Technology of Information and Communication: IT Challenges for Sustainability, Scalability, and Security in the Age of Digital Disruption, iSemantic 2020

Conference

Conference2020 International Seminar on Application for Technology of Information and Communication, iSemantic 2020
Country/TerritoryIndonesia
CitySemarang
Period19/09/2020/09/20

Keywords

  • Genetic Algorithm
  • Machine Learning
  • Maze Game
  • Procedural Content Generation

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