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复杂系统与复杂性科学  2017, Vol. 14 Issue (3): 45-57    DOI: 10.13306/j.1672-3813.2017.03.004
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基于能力组件的作战仿真Agent模块化结构设计
蒲玮, 李雄
装甲兵工程学院陆军装备作战仿真军队重点实验室,北京 100072
Modularization Structure Design for Warfare Simulation Agent Based on Capability Component
PU Wei, LI Xiong
PLA Key Laboratory of Army Equipment Warfare Simulation, Academy of Armored Forces Engineering, Beijing 100072, China
全文: PDF(2930 KB)  
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摘要 针对目前作战仿真Agent软件实现模块化程度不高、复用性较差和开发效率较低的问题,提出了一种基于Agent能力组件的作战仿真Agent模块化结构设计方法。提出了BDI模型在作战仿真Agent中的实现方式及其能力封装与能力关系的基本概念;基于能力封装,设计了作战仿真Agent能力组件的结构、要素、功能类和执行算法;基于能力关系,设计了基于能力组件的作战仿真Agent通用执行模块的结构、数据模型、功能类和执行算法。以装甲分队平台级仿真Agent的实现为例,验证了方法的可行性与有效性。
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蒲玮
李雄
关键词 Agent作战仿真能力能力组件模块化    
Abstract:To solve the problem of low degree of modularity, low reuse and low development efficiency of warfare simulation agent software, a modularization structure design method for warfare simulation agent based on capability component is proposed. The implementation of BDI model in warfare simulation agent, and the basic concept of capability encapsulation and capability relationship are proposed. The structure, element, class and executive algorithm of warfare simulation agent’s capability component based on capability encapsulation are designed. The structure, data model, class and executive algorithm of warfare simulation agent’s general executive module based on capability component are designed. An instance of platform-level armored troop warfare modeling is used to verify the feasibility and effectiveness of the method.
Key wordsagent    warfare simulation    capability    capability component    modularization
收稿日期: 2016-07-31      出版日期: 2019-01-10
ZTFLH:  TP391.9  
基金资助:国家自然科学基金(61473311);北京市自然科学基金(9142017)
作者简介: 蒲玮(1983),男,河北石家庄人,博士研究生,主要研究方向为复杂作战系统仿真、装备作战仿真等。
引用本文:   
蒲玮, 李雄. 基于能力组件的作战仿真Agent模块化结构设计[J]. 复杂系统与复杂性科学, 2017, 14(3): 45-57.
PU Wei, LI Xiong. Modularization Structure Design for Warfare Simulation Agent Based on Capability Component. Complex Systems and Complexity Science, 2017, 14(3): 45-57.
链接本文:  
http://fzkx.qdu.edu.cn/CN/10.13306/j.1672-3813.2017.03.004      或      http://fzkx.qdu.edu.cn/CN/Y2017/V14/I3/45
[1]史忠植.智能主体及其应用[M]. 北京: 科学出版社, 2000.
[2]廖守亿, 王仕成, 张金生. 复杂系统基于Agent的建模与仿真[M]. 北京: 国防工业出版社, 2015.
[3]李雄. 基于Agent的作战建模[M].北京:国防工业出版社, 2013.
[4]姜晓平, 朱奕, 伞冶. 基于复杂系统的信息化作战仿真研究进展[J]. 计算机仿真, 2014, 31(2): 813.
Jiang Xiaoping, Zhu Yi, San Ye. Survey of information-based combat simulation using complex systems theory[J]. Computer Simualtion, 2014, 31(2): 813.
[5]毛新军, 胡翠云, 孙跃坤, 等. 面向Agent程序设计的研究[J]. 软件学报, 2012, 23(11): 29232936.
Mao Xinjun, Hu Cuiyun, Sun Yuekun, et al. Research on agent-oriented programming[J]. Journal of Software, 2012, 23(11): 29232936.
[6]胡翠云, 毛新军, 陈寅. 基于组织的面向Agent程序设计及其语言Oragent[J]. 软件学报, 2012, 23(11): 28852900.
Hu Cuiyun, Mao Xinjun, Chen Yin. Organization-based agent-oriented programming and language oragent[J]. Journal of Software, 2012, 23(11): 28852900.
[7]毛新军. 面向Agent软件工程:现状、挑战与展望[J]. 计算机科学, 2011, 38(1): 17.
Mao Xinjun. State-of-the-Art, challenges and perspectives of agent-oriented software engineering[J]. Computer Science, 2011, 38(1): 17.
[8]Dam H K, Winikoff M. Towards a next-generation AOSE methodology[J]. Science of Computer Programming,2013,78(6):684694.
[9]余文广, 王维平, 李群, 等. 模型驱动的组件化Agent仿真模型开发方法[J]. 系统工程与电子技术, 2011, 33(8): 19071912.
Yu Wenguang, Wang Weiping, Li Qun, et al. Modeldriven and componentbased development method ofagentbased simulation models[J]. Systems Engineering and Electronics, 2011, 33(8): 19071912.
[10] Joao D, Samuel M, Ana P. FAtiMA modular: towards an agentarchitecture with a generic appraisalframework[J]. Lecture Notes in Computer Science, 2014, 8751(1):4456.
[11] 黄建新, 李群, 贾全, 等. 可组合的Agent体系仿真模型框架研究[J]. 系统工程与电子技术, 2011, 33(7): 15531567.
Huang Jianxin, Li Qun, Jia Quan, et al.Research on composable agent model framework for SoS[J]. System Engineering and Electronics, 2011, 33(7): 15531567.
[12] Lin P, Patrick L. Formalisations of capabilities for BDI-agents[J]. Autonomous Agents and Multi-Agent Systems, 2005, 19(10): 249271.
[13] Bratman M, Israel D, Pollack M. Plans and resource-bounded practical reasoning[J]. Computational Intelligence, 1988, 4(3): 349355.
[14] Simeon V, John T, James H, et al. Preference-based reasoning in BDI agent systems[J]. Autonomous Agents and Multi-Agent Systems, 2016, 30(2): 291330.
[15] Max W, Lin P, Sebastian S. Improving domain-independent intention seletion in BDI system[J]. Autonomous Agents and Multi-Agent Systems, 2015, 29(4): 683717.
[16] Hanen L R, Fahem K, Lamjed B S. Computational models of immediate and expected emotions for emotional BDI agents[J]. Lecture Notes in Computer Science, 2015, 9120(1): 424435.
[17] Rao A S, Georgeff M. BDI agents: from theory to practice[C]. 1st International Coference on Multi-Agent System, 1995, 312319.
[18] James H, David N M, John T, et al. An operational semantics for the goal life-cycle in BDI agents[J]. Autonomous Agents and Multi-Agent Systems, 2014, 28(4): 682719.
[19] Ingrid N. Improving the design and modularity of BDI agents with cpability relationships[J]. Lecture Notes in Computer Science, 2014, 8758(1): 5880.
[20] 蒲玮, 李雄, 陈强. 基于MaSE的多Agent作战仿真控制框架设计方法[J]. 装甲兵工程学院学报, 2015, 29(6): 6471.
Pu Wei, Li Xiong, Chen Qiang. Multi-agent warfare simulation control framework design methodbased on MaSE[J]. Journal of Academy of Armored Force Engineering, 2015, 29(6): 6471.
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