| A Non-Kinetic Behavior Modeling for Pilots Using a Hybrid Sequence Kernel |
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Yerim Choi, Sungwook Jeon, Cheolkyu Jee, Jonghun Park, Dongmin Shin |
1Department of Industrial Engineering, Seoul National University
2The 7th Research and Development Institute, Agency for Defense Development
3Department of Industrial and Management Engineering, Hanyang University |
| 혼합 시퀀스 커널을 이용한 조종사의 비동적 행위 모델링 |
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최예림, 전승욱, 지철규, 박종헌, 신동민 |
1서울대학교 산업공학과
2국방과학연구소 제7기술연구본부
3한양대학교 산업경영공학과 |
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| Abstract |
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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. |
| Key Words:
Non-Kinetic Behavior Modeling, Pilots, Hybrid Sequence Kernel, Combat Logs, Support Vector Machines |
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