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자율무기체계 지능화를 위한 시뮬레이션 기반 강화학습
Simulation Based Reinforcement Learning for the Intelligence Behavior of Autonomous Weapon System 원문보기

한국시뮬레이션학회논문지 = Journal of the Korea Society for Simulation, v.32 no.2, 2023년, pp.91 - 111  

변재현 (육군분석평가단) ,  최민우 (국방대학교 국방과학과 군사운영분석) ,  최은진 (육군사관학교 이학처 수학과) ,  송이화 ((주)풍산) ,  김진구 ((주)풍산) ,  박성택 ((주)풍산) ,  권오정 (풍산-KAIST) ,  조남석

초록
AI-Helper 아이콘AI-Helper

자율무기체계(AWS)의 막강한 군사적 파급력에도 불구하고 체계의 지능화와 관련된 실증연구는 부족한 것이 현실이다. 본 연구는 공학적인 관점에서 드론의 정찰 임무를 지능화하는데 필요한 개념에 대해 논의하고, 이를 구현하는데 필요한 기술들을 구체적으로 제시하고 실증한다. 이를 위해, 시뮬레이션 기반 학습프레임워크, 시뮬레이션 환경에서 지도학습강화학습의 연계, 항공 이미지 데이터를 이용한 비전기반 학습 등을 논의한다. 본 연구를 통해 자율무기체계의 지능화를 위한 시뮬레이션 기반 학습의 중요성과 가능성을 확인하였다. 본 연구는 AI 과학기술 강군 건설을 위한 기초연구로서 가치와 기여점이 있다.

Abstract AI-Helper 아이콘AI-Helper

Despite its strong military impact, there is a lack of empirical research related to the intelligence of Autonomous Weapon Systems (AWS). This study discusses the necessary concepts for intelligent reconnaissance missions of drones from an engineering perspective and provides concrete proposals for ...

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표/그림 (28)

참고문헌 (69)

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