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Recommendation model for battlefield analysis based on siamese network / Geewon Suh ; Yukyung Shin ; Soyeon Jin ; Woosin Lee ; Jongchul Ahn ; Changho Suh 1

Abstract 1

요약 1

I. Introduction 2

II. Background 2

1. Simulation Setting 2

2. Description of Terms 2

3. Dataset Construction 3

III. Algorithm Description 3

1. Vector Embedding 3

2. Learning Model 4

3. Ranking Algorithm 4

IV. Experimental Result 5

1. Dataset & Experiment 5

2. Pairwise Comparison Model 6

3. Score Refinement 6

V. Conclusions 7

REFERENCES 7

Authors 8

초록보기

점점 더 복잡해지고 다양해지는 무기체계와 급격하게 변화하는 전장정보에 따라서, 인공지능을 사용한 전장 상황 분석 연구의 필요성이 대두되고 있다. 본 논문에서는 전장 상황을 분석하여 현재 상황에적합한 가설을 추천해주는 분석결과 추천 학습모델의 학습 및 설계 방안을 제안한다. 학습 모델은두 가설을 비교하여 결정되는 선호 여부를 레이블 데이터로 활용하여, 어떠한 가설이 현재 전장상황을잘 분석하고 있는지 학습한다. 또한 후처리 랭킹 알고리즘을 통하여 각각의 가설에 대한 종합점수를부여하고, 점수가 높은 상위 가설들을 지휘관에게 추천할 수 있음을 확인한다.

In this paper, we propose a training method of a recommendation learning model that analyzes the battlefield situation and recommends a suitable hypothesis for the current situation. The proposed learning model uses the preference determined by comparing the two hypotheses as a label data to learn which hypothesis best analyzes the current battlefield situation. Our model is based on Siamese neural network architecture which uses the same weights on two different input vectors. The model takes two hypotheses as an input, and learns the priority between two hypotheses while sharing the same weights in the twin network. In addition, a score is given to each hypothesis through the proposed post-processing ranking algorithm, and hypotheses with a high score can be recommended to the commander in charge.

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기사명 저자명 페이지 원문 목차
Recommendation model for battlefield analysis based on siamese network Geewon Suh, Yukyung Shin, Soyeon Jin, Woosin Lee, Jongchul Ahn, Changho Suh p. 1-8

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참고문헌 (10건) : 자료제공( 네이버학술정보 )

참고문헌 목록에 대한 테이블로 번호, 참고문헌, 국회도서관 소장유무로 구성되어 있습니다.
번호 참고문헌 국회도서관 소장유무
1 C.E. Lee, J.H. Son, H.S. Park, S.Y. Lee, S.J. Park, Y.T. Lee, “Technical Trends of AI Military Staff to Support Decision-Making of Commanders,” Electronics and Telecommunications Trends, Vol. 36, No. 1, pp. 89-98, Feb. 2021. DOI: https://doi.org/10.22648/ETRI.2021.J.360110 미소장
2 F. Barlos, A. Peeke et al. “Collection and Monitoring via Planning for Active Situational Scenarios (COMPASS) (Strategic Multi-Layer Assessment Report),” STRATEGIC TECHNOLOGY OFFICE, 2020. DOI: https://doi.org/10.2172/1592839 미소장
3 DEFENSE ADVANCED RESEARCH PROJECTS DAGENCY, Active Interpretation of Disparate Alternatives, URL: https://www. darpa.mil/program/active-interpretation-of-disparate-alternatives 미소장
4 Changhee Han, Jongkwan Lee, “A Methodology for Defense AI Command & Control Platform Construction,” The Journal of Korean Institute of Communications and Information Sciences, Vol. 44, No. 4, pp. 774-781, Feb. 2019. DOI: http://dx.doi.org/10.7840/kics.2019.44.4.774 미소장
5 Changhee Han, “A Methodology for Constructing Intelligent-Machine FDC Commander Using Decision-Making Tree,” The Journal of Korea Institute of Communications and Information Sciences, Vol. 45, No. 2, pp. 355-363, Feb. 2020. DOI: https://doi.org/10.7840/kics.2020.45.2.355 미소장
6 Cho, Eunji, Soyeon Jin, Yukyung Shin, and Woosin Lee. “A Virtual Battlefield Situation Dataset Generation for Battlefield Analysis Based on Artificial Intelligence.” Journal of the Korea Society of Computer and Information 27, no. 6 (June 30, 2022):33–42. DOI: http://doi.org/10.9708/jksci.2022.27.06.033 미소장
7 Koch, Gregory, Richard Zemel, and Ruslan Salakhutdinov. "Siamese neural networks for one-shot image recognition." ICML deep learning workshop. Vol. 2. 2015. URL: http://www.cs.toro nto.edu/~gkoch/files/msc-thesis.pdf 미소장
8 Chen, Yuxin, and Changho Suh. "Spectral mle: Top-k rank aggregation from pairwise comparisons." International Conference on Machine Learning. PMLR, 2015. DOI: https://doi.org/10.48550/arXiv.1504.07218 미소장
9 Chen, Jiaoyan, et al. "Owl2vec*: Embedding of owl ontologies."Machine Learning 110.7 (2021): 1813-1845. DOI: https://doi.org/10.1007/s10994-021-05997-6 미소장
10 Negahban, S., Oh, S., and Shah, D. Rank centrality: Ranking from pair-wise comparisons. 2012. DOI: https://doi.org/10.48550/arXiv.1209.1688 미소장

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