A Multi-resolution Simulation Modeling Method

doi:10.16182/j.issn1004731x.joss.21-0778

Abstract

Abstract:

Aiming at the resolution gap between the operation task issued by the high-level commanders and the simulation system model instructions in the human-in-the-loop simulation deduction, a multi-resolution modeling method based on behavior tree is proposed. By improving the behavior tree syntax, the low-resolution combat missions are disaggregated into high-resolution simulation system instructions. By designing a decision model embedded in the behavior tree, the problem of resource uncertainty and execution effect uncertainty faced in the execution of model instructions is solved. A combat scenario for seizing air supremacy is designed to verify the effectiveness of the method.

Key words: multi-resolution model, behavior tree, resource uncertainty, effect uncertainty

CLC Number:

TP301

Zhaopeng Liu, Xinhai Xu, Bowen Yuan, Jinlu Zhang. A Multi-resolution Simulation Modeling Method[J]. Journal of System Simulation, 2023, 35(1): 202-211.

Figures/Tables 12

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References 25

1	Pace Dale K. Dimensions and Attributes of Simulation Fidelity [C]// Proceedings of 1998 Fall SIW.
2	David P K, Bigelow J. Experiments on Multiresolution Modeling(MRM) [R]. RAND Report-MR1004, 1998.
3	Davis P K, Bigelow J. Introduction to Multi-Resolution Model(MRM) with an Example Involving Precision Fires[C]// Enabling technology for Simulation Science (II). Proceeding of SPIE AeoroSense 1998.
4	刘宝宏, 黄柯棣. 多分辨率建模的研究现状与发展[J]. 系统仿真学报, 2004, 16(6): 1150-1154.
	Liu Baohong, Huang Kedi. Research Status and Development of Multi-resolution Modeling[J]. Journal of System Simulation, 2004, 16(6): 1150-1154.
5	李志飞, 吴静. 多粒度建模方法分析及实例研究[J]. 中国电子科学研究院学报, 2011, 6(1): 72-76.
	Li Zhifei, Wu Jing. Analysis of Multi-granularity Modeling Method and Case Study[J]. Journal of China Academy of Electronics, 2011, 6(1): 72-76.
6	李明忠, 毕长剑, 刘小荷, 等. 空军作战仿真模型聚合与解聚研究[J]. 系统仿真学报, 2008, 20(14): 3679-3684.
	Li Mingzhong, Bi Changjian, Liu Xiaohe, et al. Research on Aggregation and Disaggregation of Air Force Combat Simulation Models[J]. Journal of System Simulation, 2008, 20(14): 3679-3684.
7	刘宝宏, 黄柯棣. 多分辨率模型联合仿真的研究[J]. 计算机仿真, 2005, 22(2): 9-11
	Liu Baohong, Huang Kedi. Research on Co-simulation of Multi-resolution Models[J]. Computer Simulation, 2005, 22(2): 9-11.
8	Staff Joint. Universal Joint Task List[Z/OL].(2017-06-01) [2019-04-17]. .
9	王伟, 陈聪, 蒋鲁峰, 等. 兰德战略评估系统的软件设计、应用与发展[M]. 北京: 航空工业出版社, 2015.
	Wang wei, Chen Cong, Jiang Lufeng, et al. Software Design, Application and Development of RAND Strategic Evaluation System[M]. Beijing: Aviation Industry Press, 2015.
10	杨立功, 郭齐胜, 张伟. 聚合级实体仿真中任务的分解与解聚[J]. 系统仿真学报, 2006, 18(2): 186-188.
	Yang Ligong, Guo Qisheng, Zhang Wei. Decomposition and disaggregation of Tasks in Aggregation-level Entity Simulation[J]. Journal of System Simulation, 2006, 18(2):186-188.
11	荣明, 杨镜宇, 张昱. 多分辨率模型想定数据联合部署系统设计与实现[J]. 系统仿真学报, 2013, 25(增1): 318-322.
	Rong Ming, Yang Jingyu, Zhang Yu. Design and Implementation of Joint Deployment System for Multi-resolution Model Scenario Data[J]. Journal of System Simulation, 2013, 25(S1): 318-322.
12	刘剑, 薛昌友, 孙珠峰. 海战潜艇兵力作战任务聚合、解聚与重构实现[J].火力与指挥控制, 2015, 40(1): 131-136.
	Liu Jian, Xue Changyou, Sun Zhufeng. The Realization of Aggregation, Disaggregation and Reconstruction of Naval Submarine Forces Combat Missions[J]. Firepower and Command Control, 2015, 40(1): 131-136.
13	刘剑, 肖明彦, 章阳. 面向服务的舰艇编队反潜作战任务多分辨率建模研究[J]. 舰船科学技术, 2014, 36(8): 142-148.
	Liu Jian, Xiao Mingyan, Zhang Yang. Research on Service-Oriented Multi-resolution Modeling of Ship Formation Anti-submarine Combat Tasks[J]. Ship Science and Technology, 2014, 36(8): 142-148.
14	Puga G F, Gomez-Martin M A, Diaz-Agudob, et al. Dynamic Expansion of Behavior Trees[C] // Artificial Intelligence and Interactive Digital Entertainment Conference. 2008: 22-24.
15	刘瑞峰, 王家胜, 张灏龙, 等. 行为树技术的研究进展与应用[J]. 计算机与现代化工程, 2020(2): 76-82.
	Liu Ruifeng, Wang Jiasheng, Zhang Haolong, et al. Research Progress and Application of Behavior Tree Technology[J].Computer and Modern Engineering, 2020(2): 76-82.
16	董倩, 纪梦琪, 朱一凡. 空中作战决策行为树建模与仿真[J]. 指挥控制与仿真, 2019, 41(1): 18-25.
	Dong Qian, Ji Mengqi, Zhu Yifan. Air Combat Decision Behavior Tree Modeling and Simulation[J].Command Control and Simulation, 2019, 41(1): 18-25.
17	方君, 闫文君, 邓向阳, 等. 基于Q-学习和行为树的CGF空战行为决策[J]. 计算机与现代化, 2017(5): 37-39, 44.
	Fang Jun, Yan Wenjun, Deng Xiangyang, et al. CGF Air Combat Behavior Decision Based on Q Learning and Behavior Tree[J].Computer and Modernization, 2017(5): 37-39, 44.
18	涂浩, 刘洪星. 一种改进型Q 学习算法及其在行为树中的应用[J]. 计算机应用与软件, 2017, 34(12): 235-239.
	Tu Hao, Liu Hongxing. An Improved Q Learning Algorithm and Its Application in Behavior Tree[J].Computer Applications and Software,2017, 34(12): 235-239.
19	胡勇文, 陈国华. (m, n, k)指派问题的最小费用流模型及其算法[J]. 数学的实践与认知, 2017, 47(18): 162-170.
	Hu Yongwen, Chen Guohua. (m, n, k) Minimum Cost Flow Model and Algorithm for Assignment Problem[J].Practice and Cognition of Mathematics, 2017, 47(18):162-170.
20	Chen Y, Yang D, Yu J. Multi-UAV Task Assignment with Parameter and Time-sensitive Uncertainties using Modified Two-part Wolf Pack Search Algorithm[J]. IEEE Transactions on Aerospace and Electronic Systems(S1557-9603), 2018, 54(6): 2853-2872.
21	GERKEY B P. On Multi-robot Task Allocation [D]. Los Angeles: University of Southern California, 2003.
22	Jian F W, Gao W J, Jun-can L, et al. Cooperative Task Allocation for Heterogeneous Multi-UAV Using Multi-objective Optimization Algorithm[J]. Journal of Central South University (S2095-2899), 2020, 27(2): 432-448.
23	Xu G, Long T, Wang Z, et al. Target-Bundled Genetic Algorithm for Multi-unmanned Aerial Vehicle Cooperative Task Assignment Considering Precedence Constraints[J]. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering (S0954-4100), 2020, 234(3): 760-773.
24	费爱国, 张陆游, 丁前军. 基于拍卖算法的多级协同火力分配[J]. 系统工程与电子技术, 2012, 34(9): 1829-1833.
	Fei Aiguo, Zhang Luyou, Ding Qianjun. Multi-level Cooperative Fire Distribution Based on Auction Algorithm[J].System Engineering and Electronic Technology, 2012, 34(9): 1829-1833.
25	吴俊成, 周锐, 燃华明, 等. 遗传算法和拍卖算法在任务分配中的性能比较[J]. 电光与控制, 2016, 23(2): 11-15.
	Wu Juncheng, Zhou Rui, Ran Huaming, et al. Performance Comparison between Genetic Algorithm and Auction Algorithm in Task Allocation[J]. Electro-optical and control, 2016, 23(2): 11-15.

仿真结果	调用决策模型	未调用决策模型	总数
样本总数	6	3	9
完成仿真过程样本数	6	3	9
蓝方成功夺取制空权样本数	2	3	5
蓝方未成功夺取制空权样本数	4	0	4

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