행위자 기반 모델을 활용한 이동 표적 탐색 방안 연구

It is challenging to find underwater targets that move covertly in the ASW (Anti-Submarine Warfare) operations. Many studies have attempted to model this problem as an optimization problem to maximize detection probability and minimize the number of search trials. Nevertheless, the existing search algorithms have drawbacks that the search time increases dramatically as the search space expands. In addition, there are various limitations in applying the algorithm by practitioners due to the complexity of the problem. In this study, we explored the search problem with the Markov Decision Process and extended it to Agent-Based Model and Simulation (ABMS). As a result, we will not only provide a practitioner-friendly solution that requires less mathematical background as well as examining various realistic situations.