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Self-Optimizing Evaluation Function for Chinese-Chess

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  • 발행기관
    보안공학연구지원센터(IJHIT) 바로가기
  • 간행물
    International Journal of Hybrid Information Technology 바로가기
  • 통권
    Vol.7 No.4 (2014.07)바로가기
  • 페이지
    pp.163-172
  • 저자
    Xiangran Du, Min Zahang, Xizhao Wang
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A230371

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원문정보

초록

영어
Computer game is a vibrant research area in artificial intelligence. Chinese chess game is an important part of computer game and it has become an important study area after chess game had reached its culmination when Deep Blue and its successors beat Kasparov. Some achievements acquired in Chinese chess game have applied into fields of medicine, economics and military. This paper presented a new method of optimizing evaluation function in Chinese-chess programming by particle swarm optimization. The process of training evaluation function is to automatically adjust these parameters in the evaluation function by self-optimizing method accomplished through competition, which is a Chinese-chess system plays against itself with different evaluation functions. The results show that the particle swarm optimization is successfully applied to optimize the evaluation function in Chinese chess and the performance of the presented program is effectively improved after many trains. We also examined the importance of the place control in the evaluation function by the comparison the optimizing results with and without the control of the place and showed the comparison result.

목차

Abstract
 1. Introduction
 2. Evaluation Function
 3. The Optimization of the Evaluation Function
  3.1 Particle Swarm Optimization
  3.2 Optimizing Evaluation Function
 4. Experimental Results and Discussion
  4.1 Particle Swarm Optimization
  4.2 Comparison of the Optimizing Results
 5. Conclusions and Future Direction
 Acknowledgement
 References

키워드

Artificial intelligence Chinese-chess Particle swarm optimization Self-learning Evaluation function

저자

  • Xiangran Du [ Tianjin Maritime College, Tianjin 300350, China, Key Lab. of Machine Learning and Computational Intelligence, College of Mathematics and Computer Science, Hebei University, Baoding 071002, China ]
  • Min Zahang [ Tianjin Maritime College, Tianjin 300350, China ]
  • Xizhao Wang [ Key Lab. of Machine Learning and Computational Intelligence, College of Mathematics and Computer Science, Hebei University, Baoding 071002, China ]

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    보안공학연구지원센터(IJHIT) [Science & Engineering Research Support Center, Republic of Korea(IJHIT)]
  • 설립연도
    2006
  • 분야
    공학>컴퓨터학
  • 소개
    1. 보안공학에 대한 각종 조사 및 연구 2. 보안공학에 대한 응용기술 연구 및 발표 3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최 4. 보안공학 기술의 상호 협조 및 정보교환 5. 보안공학에 관한 표준화 사업 및 규격의 제정 6. 보안공학에 관한 산학연 협동의 증진 7. 국제적 학술 교류 및 기술 협력 8. 보안공학에 관한 논문지 발간 9. 기타 본 회 목적 달성에 필요한 사업

간행물

  • 간행물명
    International Journal of Hybrid Information Technology
  • 간기
    격월간
  • pISSN
    1738-9968
  • 수록기간
    2008~2016
  • 십진분류
    KDC 505 DDC 605

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