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

The Korea Institute of Military Science and Technology (한국군사과학기술학회)
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Design of Scenario Creation Model for AI-CGF based on Naval Operations, Resources Analysis Model(I): Evolutionary Learning

해군분석모델용 AI-CGF를 위한 시나리오 생성 모델 설계(I): 진화학습

  • Hyun-geun, Kim (Department of Computer Science, Graduate School, Korea Aerospace University) ;
  • Jung-seok, Gang (Department of Computer Science, Graduate School, Korea Aerospace University) ;
  • Kang-moon, Park (Dept. of Electronic Engineering, Korea National University of Transportation) ;
  • Jae-U, Kim (New Technology Research Group, Ares Co., Ltd.) ;
  • Jang-hyun, Kim (New Technology Research Group, Ares Co., Ltd.) ;
  • Bum-joon, Park (Naval Force Analysis Test Evaluation Group) ;
  • Sung-do, Chi (Department of Software, Korea Aerospace University)
  • 김현근 (한국항공대학교 대학원 컴퓨터공학과) ;
  • 강정석 (한국항공대학교 대학원 컴퓨터공학과) ;
  • 박강문 (한국교통대학교 전자공학과) ;
  • 김재우 (주식회사 아레스 신기술연구단) ;
  • 김장현 (주식회사 아레스 신기술연구단) ;
  • 박범준 (해군 전력분석시험평가단) ;
  • 지승도 (한국항공대학교 소프트웨어학과)
  • Received : 2022.07.05
  • Accepted : 2022.11.25
  • Published : 2022.12.05
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Abstract

Military training is an essential item for the fundamental problem of war. However, there has always been a problem that many resources are consumed, causing spatial and environmental pollution. The concepts of defense modeling and simulation and CGF(Computer Generated Force) using computer technology began to appear to improve this problem. The Naval Operations, Resources Analysis Model(NORAM) developed by the Republic of Korea Navy is also a DEVS(Discrete Event Simulation)-based naval virtual force analysis model. The current NORAM is a battle experiment conducted by an operator, and parameter values such as maneuver and armament operation for individual objects for each situation are evaluated. In spite of our research conducted evolutionary, supervised, reinforcement learning, in this paper, we introduce our design of a scenario creation model based on evolutionary learning using genetic algorithms. For verification, the NORAM is loaded with our model to analyze wartime engagements. Human-level tactical scenario creation capability is secured by automatically generating enemy tactical scenarios for human-designed Blue Army tactical scenarios.

Keywords

References

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