Journal of Korea Game Society (한국게임학회 논문지)

Korea Game Society (한국게임학회)
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Automatic Generation of Match-3 Game Levels using Genetic Algorithm

유전알고리즘을 이용한 Match-3 게임 레벨 자동 생성

  • 박인화 (숭실대학교 미디어학부) ;
  • 오경수 (숭실대학교 미디어학부)
  • Received : 2019.05.13
  • Accepted : 2019.06.12
  • Published : 2019.06.19
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Abstract

This paper proposes a automatic generation method of Match-3 game levels through genetic algorithm. It takes a lot of time and effort if persons have to control the level in the game. In this paper, the genetic algorithm is applied to create an appropriate block combination. We create block combination from integer DNA. Fitness is high if success probability played by computer is closer to given probability. Experiments have shown that computer-determined levels of difficulty have a significant impact on the results of game played persons.

본 논문은 유전 알고리즘을 통한 Match-3 게임의 레벨 자동 생성 방법을 제안한다. 적절한 난이도의 게임 레벨을 만들기 위하여 사람이 일일이 게임 레벨을 조절해야 한다면, 사람은 그것을 위한 많은 시간과 노력이 필요하다. 본 논문에서는 유전 알고리즘을 적용하여 Match-3 게임에서의 난이도에 맞는 블록조합을 생성한다. 각 게임 레벨의 블록조합이 진화되는 개체이다. 유전자인 정수로부터 블록조합 개체를 생성하고, 주어진 성공확률과 컴퓨터가 플레이했을 때의 성공확률이 가까워질수록 적합도가 높아지도록 설정하여 해당 블록조합을 진화시킨다. 이를 통해 게임 난이도에 맞는 적절한 블록조합들을 생성하는 데 성공하였으며, 실험한 결과 컴퓨터가 결정한 난이도가 실제 사람이 게임했을 때의 결과에 영향을 준다는 것을 확인하였다.

Keywords

KGOHCL_2019_v19n3_25_f0001.png 이미지

[Fig. 1] Scene about Playing Match-3 Game

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[Fig. 2] Block Combination of Stage 1

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[Fig. 3] Block Combination of Stage 2

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[Fig. 4] Block Combination of Stage 3

[Table 1] Block Combinations by Genetic Algorithm

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[Table 2] Success Probability by Played Persons

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[Table 3] Comparison of the Average Score According to the Order of Game Stage

KGOHCL_2019_v19n3_25_t0003.png 이미지

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