Journal of the Korea Institute of Military Science and Technology (한국군사과학기술학회지)

The Korea Institute of Military Science and Technology (한국군사과학기술학회)
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A Non-Kinetic Behavior Modeling for Pilots Using a Hybrid Sequence Kernel

혼합 시퀀스 커널을 이용한 조종사의 비동적 행위 모델링

  • Choi, Yerim (Department of Industrial Engineering, Seoul National University) ;
  • Jeon, Sungwook (Department of Industrial Engineering, Seoul National University) ;
  • Jee, Cheolkyu (The 7th Research and Development Institute, Agency for Defense Development) ;
  • Park, Jonghun (Department of Industrial Engineering, Seoul National University) ;
  • Shin, Dongmin (Department of Industrial and Management Engineering, Hanyang University)
  • 최예림 (서울대학교 산업공학과) ;
  • 전승욱 (서울대학교 산업공학과) ;
  • 지철규 (국방과학연구소 제7기술연구본부) ;
  • 박종헌 (서울대학교 산업공학과) ;
  • 신동민 (한양대학교 산업경영공학과)
  • Received : 2014.03.07
  • Accepted : 2014.11.07
  • Published : 2014.12.05
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Abstract

For decades, modeling of pilots has been intensively studied due to its advantages in reducing costs for training and enhancing safety of pilots. In particular, research for modeling of pilots' non-kinetic behaviors which refer to the decisions made by pilots is beneficial as the expertise of pilots can be inherent in the models. With the recent growth in the amount of combat logs accumulated, employing statistical learning methods for the modeling becomes possible. However, the combat logs consist of heterogeneous data that are not only continuous or discrete but also sequence independent or dependent, making it difficult to directly applying the learning methods without modifications. Therefore, in this paper, we present a kernel function named hybrid sequence kernel which addresses the problem by using multiple kernel learning methods. Based on the empirical experiments by using combat logs obtained from a simulator, the proposed kernel showed satisfactory results.

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References

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