한국산업정보학회논문지 (Journal of Korea Society of Industrial Information Systems)

한국산업정보학회 (Korea Society of Industrial Information Systems)
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사건 발생 확률 변화를 고려한 에이전트-타깃 감지 문제

Agent-target Detection Problem Considering Change in Probability of Event Occurrence

  • 김광 (조선대학교 경영학부)
  • Gwang Kim
  • 투고 : 2024.07.15
  • 심사 : 2024.08.14
  • 발행 : 2024.08.30
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초록

본 연구에서는 다중 에이전트를 이용한 타깃 감지 문제를 다루는데, 특히 이동식 에이전트를 활용한 감지 문제는 경로 계획에 대한 전략이 추가로 필요하다. 문제의 목표는 특정 기간 내 감지 프로세스를 통해 총 효용을 극대화할 수 있는 각 에이전트의 경로를 찾는 것인데, 시간에 따라 타깃의 사건 발생 확률이 변하도록 하는 포아송 프로세스(Poisson process) 기반의 확률적 프로세스(stochastic process)를 고려하여 현실적인 효용 값을 반영한다. 본 감지 문제의 목적함수는 비선형(non-linearity)이고, NP-난해(NP-hard) 문제로 표현된다. 효율적인 계산 시간 내에 효과적인 해를 찾기 위해, 본 연구에서는 하위모듈성(submodularity)의 특성을 갖는 목적함수임을 증명하고, 이를 활용해 비교적 낮은 계산 시간으로 합리적인 전략을 얻기 위한 휴리스틱 알고리즘을 제안한다. 제안한 알고리즘은 해의 성능과 적절한 계산 시간 내에 해를 도출할 수 있다는 측면에서 우수한 알고리즘임을 이론 및 실험적으로 제시한다.

In this study, we address the problem of target detection using multiple agents. Specifically, the detection problem involving mobile agents necessitates additional strategies for path planning. The objective is to maximize the total utility derived from the detection process over a specific period. This detection problem incorporates realistic utility values by considering a stochastic process based on the Poisson process, which accounts for the changing probability of target event occurrence over time. The objective function is nonlinear and is classified as an NP-hard problem. To identify an effective solution within an efficient computation time, this study demonstrates that the objective function possesses the characteristic of submodularity. Using this property, we propose a heuristic algorithm designed to obtain a reasonable strategy with relatively low computational time. The proposed algorithm shows solution performance and the ability to generate solutions within an appropriate computation time through theoretical and experimental results.

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과제정보

이 논문은 2024학년도 조선대학교 학술연구비의 지원을 받아 연구되었음.

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