Research on Target Threat Assessment in Wargaming Using the Adversarial Interpretive Structure Modeling Method
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-9021-4_42
Reference20 articles.
1. Sun, Y.X., Yuan, B., Xiang, Q., Zhou, J.W., Yu, J.H., Dai, D., Zhou, X.Z.: Intelligent decision-making and human language communication based on deep reinforcement learning in a wargame environment. IEEE Trans. Hum. Mach. Syst. 53(1), 201–214 (2023)
2. Liu, L., Xiao, L.P., Li, X.L.: Simulation of migration of hexavalent chromium in groundwater. J. Syst. Simul. 30(2), 560 (2018)
3. Davis, P.K., Bracken, P.J.: Artificial intelligence for wargaming and modeling. J. Defense Model. Simul. Appl. Methodol. Technol. (2022)
4. Gao, Y., Li, D.S., Zhong, H.: A novel target threat assessment method based on three-way decisions under intuitionistic fuzzy multi-attribute decision making environment. Eng. Appl. Artif. Intell. 87, 103276 (2020)
5. Xue, Y.F., Sun, Y.X., Zhou, J.W., Peng, L.S., Zhou, X.Z.: Multi-attribute decision-making in wargames leveraging the entropy-weight method in conjunction with deep reinforcement learning. IEEE Trans. Games 1–12 (2023)
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