Journal of Internet Computing and Services (인터넷정보학회논문지)

Korean Society for Internet Information (한국인터넷정보학회)
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Improvement of Sequential Prediction Algorithm for Player's Action Prediction

플레이어 행동예측을 위한 순차예측 알고리즘의 개선

  • 신용우 (동아방송예술대학 디지털영상과) ;
  • 정태충 (경희대학교 컴퓨터공학과)
  • Received : 2010.01.25
  • Accepted : 2010.04.26
  • Published : 2010.06.30
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Abstract

It takes quite amount of time to study a game because there are many game characters and different stages are exist for games. This paper used reinforcement learning algorithm for characters to learn, and so they can move intelligently. On learning early, the learning speed becomes slow. Improved sequential prediction method was used to improve the speed of learning. To compare a normal learning to an improved one, a game was created. As a result, improved character‘s ability was improved 30% on learning speed.

게임은 여러 캐릭터와 상태공간을 갖고 있다. 그러므로 학습을 하는데 많은 시간이 걸린다. 본 논문에서는 강화학습 알고리즘을 이용하였다. 보상 값을 받아 캐릭터가 학습하게 하여 지능적으로 움직이게 하였다. 학습초기에는 학습속도가 느려진다. 순차예측 알고리즘을 개선하여 학습에 적용하였다. 기존 강화학습으로 구현된 게임과 비교 실험하였다. 실험결과 개선 구현된 게임의 성능이 학습속도 측면에서 30% 까지 향상됨을 알 수 있었다.

Keywords

References

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